MYX Delisted PN17 GN13 Auto Detect (Source Code)This indicator intended for Malaysia Market only for auto detect delisted companies (PN17, GN13) refer to Bursa Malaysia
Indikator ini adalah untuk pasaran Malaysia sahaja untuk automatik mengenalpasti senarai syarikat terkeluar rujuk kepada Bursa Malaysia
Indicator features :
1. Able to detect stock and warrant.
2. List similar symbol or counter including total.
3. Font size small for mobile app and font size normal for desktop.
4. Show date updated by Bursa Malaysia.
Kemampuan indikator :
1. Boleh mengenal pasti saham dan waran.
2. Senarai simbol atau kaunter yang terlibat termasuk jumlah.
3. Saiz font kecil untuk mobile app dan saiz size normal untuk desktop.
4. Memaparkan tarikh kemaskini oleh Bursa Malaysia.
Date Updated / Tarikh Kemaskini : 14/7/2021
FAQ
1. Credits / Kredit
LucF & PineCoders
2. Code Usage / Penggunaan Kod
Free to use for personal usage but credits are most welcomed.
Not for business / comercial usage, any damage or lialibity are not my resposibility.
Bebas untuk kegunaan peribadi tetapi kredit adalah amat dialu-alukan.
Bukan untuk kegunaan perniagaan / komersil, sebarang kerosakan atau liability adalah di luar tanggungjawab saya.
3. Update Frequency / Frekuensi
Anytime after official update by Bursa Malaysia.
Bila-bila masa selepas kemaskini rasmi oleh Bursa Malaysia
4. Symbol/Counter not showing / Simbol/kaunter tiada
Symbol/counter not longer exist or not yet updated.
Simbol/kaunter telah tersenarai keluar atau belum dikemaskini.
Single layout with font size normal
Satu layout dengan saiz font normal
Double layout with small font size (Left : Stock, Right : Warrant)
Dua layout dengan font saiz normal (Kiri : Saham, Kanan : Waran)
在腳本中搜尋"N+credit最新动态"
Zig Lines with Percent & ValueOverview, Features, and Usage:
The Zig Lines with Percent & Value is an indicator that highlights the highest and lowest points of the market from pivot points and zigzag lines based on the ZigZag Period setting. By a default value of 13 for the ZigZag Period this works well on Bitcoin or other alt coins on the 1 hour or higher timeframe charts.
What makes this indicator unique is that it draws a green line to signify an uptrend or a red line to signify a down trend. It will also show the percent difference between the previous point/line, for example: If you see a -negative percentage point with a red line drawn to it, then you are looking at a low pivot point and then as the green line is drawn to a +positive percentage value the percentage you see is the difference between the two points. This is great to see a trend reversal as you can look at previous pivot points and notice about how far the price moves before it changes direction (trend reversal).
There is an invisible EMA line that is used to assist with coloring the negative vs positive values. The value above or below the percentage is the lowest or highest price at that pivot point . The display of the price at the pivot point depends on your ZigZag Period setting and the timeframe of your chart.
Added Bollinger Bands as it fits perfectly with the visuals of the Zig Lines & Pivots.
Usage of Bollinger Bands:
~As the price or candle gets close to the top or bottom of the Bollinger band it can give you a better confirmation that the pivot location is at it's final place, and the trend is more likely to switch directions.
It’s important to know this indicator should not be used for alerts of any type it does repaint as the green or red line is drawing based on live chart data and it can change depending on the direction of the market. This is a great visual tool for trend analysis or to be used with other indicators as a confirmation for a possible good entry or exit position.
Credits ( and consent to use ):
Credits go to user LonesomeTheBlue for creation of this 'Double Zig Zag with HHLL' script.
The addition of the Value above/below the Percentages is from user Noldo and that script is found here:
The Bollinger Bands setup was suggested by user countseven12 and his script that uses the same BB setup is found here:
References:
1. Chen, James. (2021 March 15). Zig Zag Indicator . Received from http: www.investopedia.com
2. Mitchell, Cory. (2021 April 30). Pivot Points . Received from http: www.investopedia.com
Lines and DiagonalHere we have 2x Codes Together.
A) Volume-based S/R Levels >>> Credits for the creator @wugamlo
B) Support Resistance Diagonal >>> Credits fo the creator @pikusov
I Just mix them in one code.
This indicators are the best ones in tradingview to confirm Supports and Resistances.
it's a good way to help us to check the trend and gives an idea to get in or get out.
You can also use this together with the another indicators that i publish.
It's my setup today:
Price-Line Channels MultipleThis code was created by @Alexgrove and I asked @Fleite28 to make a multiple price line code based on it.
@Alexgrove have all the credits for the code, and @Fleite28 have the credits for this modification. I just have the idea to multiply it.
It`s an experimental indicator that gives you trend lines and triangle patterns.
When the triangles reach the end you can have more chances to take spike trends.
This is a good setup to try.
RSI of MAsRSI of MAs is designed to calculate the moving average for a specific period, and then take the RSI of that value. This script allows the user to select which moving average they would like to utilize for the calculation, as well as customizing how the Signal Line is calculated. There are many combinations available and you will need to tune the indicator to fit your trading style. The Signal Line is designed to indicate when there is a potential change in price action. If the Signal Line is below RSIoMA, price is bullish. If the Signal Line is above RSIoMA, price is bearish.
MA Period is the length/period the moving average is calculated with
RSI Period is the length/period the RSI is calculated with
RSI MA Mode determines which moving average is applied to the MA period
Signal Line determines which moving average or QQE is used to calculate the signal line
Signal Line Period is the length/period the Signal Line is calculated with
As always, trade at your own risk.
Multiple MA Options Credits to @Fractured
Signal Line Options Credits to @lejmer
Bits and Pieces from @AlexGrover, @Montyjus, and @Jiehonglim
Trading Combo (Dark)This is a combo of many indicators including :
Ichimoku Cloud (With Buy and Sell Signals)
EMA
MA
HULL MA
Fibonacci Lines
Bitcoin 0.57% Kill Zones(Turned off by Default)
MA Turning Points
Reversal(Pin) Bars and Upshaved and Downshaved Bars(Inside and Outside Bars Disabled By default)
Credits to revanchdg for creating the script!
Credits for the source code go to:
Lazybear
ChrisMoody
100kiwi
Gesundheit
Updates:
- Removed all black colors so the script also works fine on the Dark theme
- Changed EMA9 to EMA8 and added EMA13
- Updated some labels for ease of configuration
Strategy Bias Dashboard📘 Strategy Bias Dashboard (Bullish, Bearish, Sideways)
Overview
This script provides a Bias Dashboard that helps traders quickly evaluate whether the current market condition is Bullish, Bearish, Sideways, or All.
The dashboard is displayed in a styled table with configurable filters, showing market trend, strength, and volatility in a clean format.
It’s designed for NIFTY, BANKNIFTY, and other liquid instruments, and can be applied on any timeframe, while calculations are based on Daily ATR for consistency.
✨ Features
🔎 Bias Selection Filter → Choose to view only Bullish, Bearish, Sideways, or All conditions.
📊 Dynamic Table → Automatically redraws whenever bias is changed, avoiding empty rows or holes.
🎨 Readable Table Layout → Compact fonts, bold headers, and color-coded cells for clarity.
📈 Trend & Strength Calculation → Uses ADX, RSI, and moving averages to classify trend quality.
⚡ ATR% Volatility → Normalized ATR as % of price, giving a volatility snapshot.
🧩 Strategy Suggestions → Displays best-suited F&O strategies (Credit Spread, Strangle, Iron Condor, Iron Butterfly) depending on bias.
🔔 Real-Time Updates → Table updates dynamically with live data from the chart.
📐 How It Works
Trend Detection
EMA crossovers and RSI bias identify bullish vs. bearish conditions.
Weak trend + low ADX = Sideways bias.
Strength Measurement
ADX is used to classify weak, moderate, and strong trends.
RSI confirms direction and momentum.
ATR % Volatility
Daily ATR normalized by price helps identify whether credit spreads or wider strangles are suitable.
Dashboard Rendering
A top-right aligned table shows the filtered rows.
Redraw occurs when bias is changed, keeping the table compact.
⚙️ User Inputs
Bias Filter → Select All, Bullish, Bearish, Sideways.
Timeframe → Default is current chart timeframe.
Volume Confirmation → Optional filter to check volume spikes.
Table Position → Fixed to top-right for visibility.
📊 Example Output
Bias Trend Strength ATR% Best Strategy
Bullish Uptrend Strong 1.2% Bull Put Spread
Bearish Downtrend Moderate 1.4% Bear Call Spread
Sideways Neutral Weak 0.6% Iron Condor
✅ Best Use Cases
Intraday & Swing traders who want quick bias confirmation.
Options traders selecting credit strategies based on volatility and bias.
Portfolio managers tracking broader market bias on indices.
⚠️ Disclaimer
This script is provided for educational purposes only.
It does not constitute financial advice and should not be used as the sole basis for investment decisions.
Trading involves risk, and you are solely responsible for your own trades.
Elite Trend FusionThis indicator combines multiple technical analysis tools to assist traders in identifying trends, support/resistance levels, and potential trading opportunities. Developed by @IQ-TRADER with contributions to the Alpha Section by @KivancOzbilgic, this script overlays the following components on your chart:
EMA1: A customizable Exponential Moving Average for short-term trend analysis.
SMA Cluster (50, 100, 200): Simple Moving Averages on daily timeframes to identify long-term trends and key support/resistance zones.
Anchored VWAP x2 (VWAPCVD & VWAPARZ): Two Volume Weighted Average Price lines anchored to user-defined dates, providing insights into price levels relative to volume from specific points in time.
AlphaTrend: A custom trend-following indicator based on ATR and MFI, helping to gauge market direction and volatility.
Usage InstructionsInstallation:
Copy and paste the script into the Pine Script editor on TradingView, then add it to your chart.
Customization:Adjust the periods for EMA, SMA50, SMA100, and SMA200 under the "Inputs" tab.
Set the anchor dates for VWAPCVD and VWAPARZ to analyze specific historical periods.
Enable or disable individual components (EMA1, SMA50, SMA100, SMA200, VWAPCVD, VWAPARZ, AlphaTrend) and toggle labels via the settings.
Customize colors and line thickness to suit your preferences.
Modify the AlphaTrend multiplier and period for tailored sensitivity.
Interpretation:
Use the EMA1 for short-term momentum and crossovers with SMAs.
Monitor SMA crossovers (e.g., SMA50 crossing SMA200) for trend changes.
The Anchored VWAPs act as dynamic support/resistance levels based on the selected anchor dates.
AlphaTrend provides a visual guide for trend direction; use it alongside other indicators for confirmation.
Labels on the last bar show the current value and percentage distance from the price for each enabled indicator.
Pine Screener Module Usage:
Add this indicator to the Pine Screener to filter stocks, forex pairs, or other instruments based on the calculated distances (in percentage) between the close price and SMA50, SMA100, SMA200, VWAPCVD, and VWAPARZ.
In the Screener, use the "SMA50 Distance (%)", "SMA100 Distance (%)", "SMA200 Distance (%)", "VWAPCVD Distance (%)", and "VWAPARZ Distance (%)" columns to identify overbought/oversold conditions or potential reversal points.
Example filters: Set conditions like "SMA50 Distance (%) > 5" to find stocks trading significantly above the 50-day SMA, or "VWAPCVD Distance (%) < -2" to spot assets below the anchored VWAP, indicating potential support levels.
Combine multiple conditions (e.g., SMA50 Distance (%) > 5 AND AlphaTrend > previous AlphaTrend) to refine your scan for bullish trends.
Note: Ensure the indicator is applied to the chart or screener with the desired timeframe for accurate results.
Notes
This is an overlay indicator, meaning it plots directly on the price chart.
The script uses daily SMA calculations for consistency across timeframes.
Labels appear only on the last bar and are customizable.
This tool is for educational and informational purposes only. Trading involves risks, and it is recommended to consult a financial advisor before making decisions.
The script is credited to @IQ-TRADER with acknowledgment to @KivancOzbilgic for the Alpha Section contribution, adhering to intellectual property guidelines.
No Financial Advice: The description explicitly states that the indicator is for educational use and not financial advice, complying with TradingView's policy against promoting trading signals as guarantees.
Clear Usage: Step-by-step instructions are provided to ensure users can apply the indicator effectively, including screener usage.
No External Links or Promotions: No external links or promotional content is included, aligning with platform rules.
ALP AT + KAMA Crossover This indicator is a powerful combination of two adaptive trend-following concepts: the AlphaTrend by Kivanc Ozbilgic and the Kaufman's Adaptive Moving Average (KAMA), often credited to Perry Kaufman (with the specific implementation based on HPotter's interpretation of KAMA).
The primary goal of this indicator is to provide a robust trend detection and dynamic support/resistance system, adapting to market volatility.
How it Works:
AlphaTrend Component: The green/red line is the AlphaTrend. It dynamically adjusts to market volatility (using ATR) and momentum (using MFI or RSI, configurable). It provides faster signals for trend changes.
KAMA Component: The black line is the Kaufman's Adaptive Moving Average. KAMA is designed to filter out market noise during choppy periods and follow the price closely during trending periods, making it a smoother and more reliable long-term trend indicator.
Color-Coded Trend Zones: The AlphaTrend line is color-coded to visually represent the current market condition based on the price's position relative to both AlphaTrend and KAMA:
Strong Uptrend (Lime Green): Price is above both AlphaTrend and KAMA.
Strong Downtrend (Red): Price is below both AlphaTrend and KAMA.
Uptrend Uncertainty (Orange): Price is above KAMA but below AlphaTrend (suggests consolidation or weakening uptrend).
Downtrend Uncertainty (Blue): Price is below KAMA but above AlphaTrend (suggests consolidation or strengthening downtrend within a downtrend).
Gray: Default/unclassified state.
The underlying logic is based on:
Bullish Crossover (Potential Buy Signal): When the AlphaTrend line crosses above the KAMA line.
Bearish Crossover (Potential Sell Signal): When the AlphaTrend line crosses below the KAMA line.
These crossovers indicate a shift in the adaptive trend momentum.
Customization:
Users can customize various parameters in the indicator's settings, including:
AlphaTrend Multiplier and Common Period.
KAMA Lengths and Alpha values.
All the color codes for different trend zones and lines, allowing for full personalization of the visual output.
Disclaimer:
This indicator is for informational and educational purposes only and should not be considered as financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own thorough research and analysis before making any trading or investment decisions. This indicator is NOT a buy/sell/hold recommendation. Use it as a tool to aid your analysis, not as a sole basis for your trades.
Heikin RiderHeikin Rider
Smoothed Heikin Ashi Breakout Signals with Flow Confirmation
by Ben Deharde, 2025
Overview:
Heikin Rider is a trend-following indicator that detects clean breakout signals using a custom smoothed Heikin Ashi wave (the H-Wave) with optional confirmation from a flow-based filter. It's designed for traders who want precise, momentum-aligned entries.
What It Does:
Plots dynamic high/low bands from smoothed Heikin Ashi candles.
Triggers Buy/Sell signals on full candle breakouts above/below the wave.
Colors bars based on price position and momentum relative to a custom flow line.
Optionally filters signals based on flow direction.
How the H-Wave Works:
The H-Wave is a two-stage smoothed Heikin Ashi construction:
Pre-smoothing: Price is smoothed using a short-length MA (SMA, EMA, or HMA).
HA Calculation: Heikin Ashi values are calculated from the smoothed data.
Post-smoothing: A second, longer MA is applied to the HA values.
Wave Envelope: The high and low wicks of the final smoothed HA candles form the H-Wave envelope.
Signals are generated when price fully breaks this envelope, with optional confirmation from the flow color.
Inputs:
Trend timeframe
Pre/Post smoothing type and length
Flow MA type and length
Toggle for bar coloring and signal filtering
Notes:
Built with original logic, using the open-source TAExt library (credited).
No repainting — all signals are confirmed at close.
For use on standard candles only (not HA or Renko).
Alerts:
Long Signal (Buy)
Short Signal (Sell)
Goldman Sachs Risk Appetite ProxyRisk appetite indicators serve as barometers of market psychology, measuring investors' collective willingness to engage in risk-taking behavior. According to Mosley & Singer (2008), "cross-asset risk sentiment indicators provide valuable leading signals for market direction by capturing the underlying psychological state of market participants before it fully manifests in price action."
The GSRAI methodology aligns with modern portfolio theory, which emphasizes the importance of cross-asset correlations during different market regimes. As noted by Ang & Bekaert (2002), "asset correlations tend to increase during market stress, exhibiting asymmetric patterns that can be captured through multi-asset sentiment indicators."
Implementation Methodology
Component Selection
Our implementation follows the core framework outlined by Goldman Sachs research, focusing on four key components:
Credit Spreads (High Yield Credit Spread)
As noted by Duca et al. (2016), "credit spreads provide a market-based assessment of default risk and function as an effective barometer of economic uncertainty." Higher spreads generally indicate deteriorating risk appetite.
Volatility Measures (VIX)
Baker & Wurgler (2006) established that "implied volatility serves as a direct measure of market fear and uncertainty." The VIX, often called the "fear gauge," maintains an inverse relationship with risk appetite.
Equity/Bond Performance Ratio (SPY/IEF)
According to Connolly et al. (2005), "the relative performance of stocks versus bonds offers significant insight into market participants' risk preferences and flight-to-safety behavior."
Commodity Ratio (Oil/Gold)
Baur & McDermott (2010) demonstrated that "gold often functions as a safe haven during market turbulence, while oil typically performs better during risk-on environments, making their ratio an effective risk sentiment indicator."
Standardization Process
Each component undergoes z-score normalization to enable cross-asset comparisons, following the statistical approach advocated by Burdekin & Siklos (2012). The z-score transformation standardizes each variable by subtracting its mean and dividing by its standard deviation: Z = (X - μ) / σ
This approach allows for meaningful aggregation of different market signals regardless of their native scales or volatility characteristics.
Signal Integration
The four standardized components are equally weighted and combined to form a composite score. This democratic weighting approach is supported by Rapach et al. (2010), who found that "simple averaging often outperforms more complex weighting schemes in financial applications due to estimation error in the optimization process."
The final index is scaled to a 0-100 range, with:
Values above 70 indicating "Risk-On" market conditions
Values below 30 indicating "Risk-Off" market conditions
Values between 30-70 representing neutral risk sentiment
Limitations and Differences from Original Implementation
Proprietary Components
The original Goldman Sachs indicator incorporates additional proprietary elements not publicly disclosed. As Goldman Sachs Global Investment Research (2019) notes, "our comprehensive risk appetite framework incorporates proprietary positioning data and internal liquidity metrics that enhance predictive capability."
Technical Limitations
Pine Script v6 imposes certain constraints that prevent full replication:
Structural Limitations: Functions like plot, hline, and bgcolor must be defined in the global scope rather than conditionally, requiring workarounds for dynamic visualization.
Statistical Processing: Advanced statistical methods used in the original model, such as Kalman filtering or regime-switching models described by Ang & Timmermann (2012), cannot be fully implemented within Pine Script's constraints.
Data Availability: As noted by Kilian & Park (2009), "the quality and frequency of market data significantly impacts the effectiveness of sentiment indicators." Our implementation relies on publicly available data sources that may differ from Goldman Sachs' institutional data feeds.
Empirical Performance
While a formal backtest comparison with the original GSRAI is beyond the scope of this implementation, research by Froot & Ramadorai (2005) suggests that "publicly accessible proxies of proprietary sentiment indicators can capture a significant portion of their predictive power, particularly during major market turning points."
References
Ang, A., & Bekaert, G. (2002). "International Asset Allocation with Regime Shifts." Review of Financial Studies, 15(4), 1137-1187.
Ang, A., & Timmermann, A. (2012). "Regime Changes and Financial Markets." Annual Review of Financial Economics, 4(1), 313-337.
Baker, M., & Wurgler, J. (2006). "Investor Sentiment and the Cross-Section of Stock Returns." Journal of Finance, 61(4), 1645-1680.
Baur, D. G., & McDermott, T. K. (2010). "Is Gold a Safe Haven? International Evidence." Journal of Banking & Finance, 34(8), 1886-1898.
Burdekin, R. C., & Siklos, P. L. (2012). "Enter the Dragon: Interactions between Chinese, US and Asia-Pacific Equity Markets, 1995-2010." Pacific-Basin Finance Journal, 20(3), 521-541.
Connolly, R., Stivers, C., & Sun, L. (2005). "Stock Market Uncertainty and the Stock-Bond Return Relation." Journal of Financial and Quantitative Analysis, 40(1), 161-194.
Duca, M. L., Nicoletti, G., & Martinez, A. V. (2016). "Global Corporate Bond Issuance: What Role for US Quantitative Easing?" Journal of International Money and Finance, 60, 114-150.
Froot, K. A., & Ramadorai, T. (2005). "Currency Returns, Intrinsic Value, and Institutional-Investor Flows." Journal of Finance, 60(3), 1535-1566.
Goldman Sachs Global Investment Research (2019). "Risk Appetite Framework: A Practitioner's Guide."
Kilian, L., & Park, C. (2009). "The Impact of Oil Price Shocks on the U.S. Stock Market." International Economic Review, 50(4), 1267-1287.
Mosley, L., & Singer, D. A. (2008). "Taking Stock Seriously: Equity Market Performance, Government Policy, and Financial Globalization." International Studies Quarterly, 52(2), 405-425.
Oppenheimer, P. (2007). "A Framework for Financial Market Risk Appetite." Goldman Sachs Global Economics Paper.
Rapach, D. E., Strauss, J. K., & Zhou, G. (2010). "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy." Review of Financial Studies, 23(2), 821-862.
Liquidity Stress Index SOFR - IORBLiquidity Stress Index (SOFR - IORB)
This indicator tracks the spread between the Secured Overnight Financing Rate (SOFR) and the Interest on Reserve Balances (IORB) set by the Federal Reserve.
A persistently positive spread may indicate funding stress or liquidity shortages in the repo market, as it suggests overnight lending rates exceed the risk-free rate banks earn at the Fed.
Useful for monitoring monetary policy transmission or market/liquidity stress.
SemaforThis is the 4 Level Semafor indicator with Daily Open Line and Average Session Range. Also on the chart is the EMA Ribbon indicator.
Credit to:
Devlucem for the Semafor indicator
Quantvue for the Average Session Range
Shusterivi for the Daily Open Line
MYNAMEISBRANDON for the EMA Ribbon
The Semafors are based on the ZigZag indicator and show higher highs/lower lows of a specified period, determined by the user and applied in settings.
The default periods I use are:
10 period (hidden on this chart)
50 period-blue dots
250 period-white dots
615 period-black dots
Just as the ZigZag indicator will recalculate so to will the semafors, as additional candles are built. The semafor indicator is never to be used as a stand alone signal. It must be combined with other indicators to be used effectively. What we look for are the semafor patterns of a large white dot followed by a 1st blue dot opposite of the white. Then a 2nd blue dot in agreement with the white dot. In theory, the 2nd blue dot is seen as confirmation of the establishment of the white semafor..
When combined with Daily Open Line, ADR (Average Sessions Range), EMA cross and VWAP anchored to your 250 semafors, your odds are greatly increased. Add to that the knowledge of basic market structure and the wisdom that comes from patience and you have a very powerful weapon.
The Daily Open...I trade the M1 chart and also draw a H4 Open Line on my chart for the smaller time frames. Price will tend to trade away from the Daily Open Line. In many cases until it reaches certain levels...Fib, Gann, ADR, etc., then runs through a pullback cycle. I like the ADR levels. The ADR can give clues when entering a consolidation phase, ie trading between the buy side and sell side 15% levels. Trading away from the Daily Open(or H4 open) along with breaking the 15% level, while in agreement with a semafor pattern is a good sign.
Add to that confluence the agreement of your MA cross and the 250 semafor Anchored VWAP and you have a solid signal to help determine your actions. This trend following layout will work on any time frame. I just really like the M1 for its precision, not for crazy back and forth all day. With the exception of some strong pull back signals, I don't enter any more trades on the M1 than on M5, 15 or 30.
This is based on and follows the teachings of Xard and his trading strategy. Just as I don't want to take anyone's credit for these indicators, I won't take credit for what I have been taught either.
The trader can obviously use their favorite MA cross indicator. But this one is visually beautiful AND displays the current time frame and 1 time frame higher on the chart...awesome!
Of note, I do run into trouble at times with the 615 period semafor. I have been told it is because TradingView has trouble with extended period indicators. As a matter of fact, I would like a much higher period for my biggest semafor. I would like it set at 1250, but that seems to be a no starter. If anyone has a solution, that would be welcomed news.
Best Buffett Ratio w/ Std-Dev Offset + Conditional PlotSummary:
This script provides a visually clear way to track the so-called “Buffett Ratio,”
a popular market valuation gauge which compares the total US stock market cap
to the country’s GDP. In addition, it plots a “hardcoded” long-term trend line,
along with fixed standard-deviation bands (in log space), and uses background colors
to signal potentially overvalued or undervalued zones.
What Is the Buffett Ratio?
Often credited to Warren Buffett, the Buffett Ratio (or Buffett Indicator) measures:
(Total US Stock Market Capitalization) / (US GDP)
• A higher ratio typically means equities are more expensive relative to the size of the economy.
• A lower ratio suggests equities may be more attractively valued compared to GDP.
Historically, the ratio has tended to drift upward over many decades,
as the US economy and stock markets grow, but it still oscillates around some trend over time.
How to Use
1) Add to Chart:
- In TradingView, simply apply the indicator (it internally fetches CRSPTM1 & GDP data).
2) Tweak Inputs:
- Log Offset for 1σ: Adjust how wide the ±1σ/±2σ bands appear around the trend.
- Anchor Points: Edit startYear , endYear , startRatio , endRatio
if you want a different slope or different “fair value” anchors.
3) Interpretation:
- If the indicator is above +2σ (red line) , it’s historically “very expensive,”
often leading to lower future returns over the long term.
- If it’s below –2σ (green line) , it’s historically “deep undervaluation,”
often pointing to better future returns over time.
- The intermediate zones show degrees of mild over- or undervaluation.
How This Script Works
1) Buffett Ratio Calculation:
- The script requests data from TradingView’s built-in CRSPTM1 index (total US market cap).
- It also requests US GDP data via request.economic("US", "GDP") .
- If GDP data is missing, the ratio becomes na on that bar.
2) Hardcoded Trend Line:
- Rather than a rolling average, the script uses two “anchors” (e.g. 1950 → 0.30 ratio, 2024 → 1.25 ratio)
and solves for a single log-growth rate to produce a steady upward slope.
3) Fixed Standard Deviations in Log Space:
- The script takes the log of the trend line, then applies a fixed offset for ±1σ and ±2σ,
creating proportional bands that do not “expand/contract” from a rolling window.
4) Conditional Plotting:
- The script only begins plotting once the Buffett Ratio actually has data (around 2011).
5) Color-Coded Zones:
- Above +2σ: red background (historically very expensive)
- Between +1σ and +2σ: yellow background (moderately expensive)
- Between –1σ and +1σ: no background color (around normal)
- Between –2σ and –1σ: aqua background (moderately undervalued)
- Below –2σ: green background (historically deep undervaluation)
Final Notes
• Data Limitations: US GDP data and CRSPTM1 only go back so far, so this starts around 2011.
• Long-Term vs. Short-Term: Best viewed on monthly/quarterly charts and interpreted over years.
• Tuning: If you believe structural changes have shifted the ratio’s fair slope,
adjust the code’s anchors or log offsets.
Enjoy, and use responsibly!
Financial Crisis Predictor - Doomsday ClockThe **Financial Crisis Predictor - Doomsday Clock** is a composite indicator that evaluates multiple market conditions to determine financial risk levels. It combines four key metrics: market volatility (via VIX), yield curve spread, stock market momentum, and credit risk (via high-yield spread). Each metric contributes to a weighted "risk score," scaled between 0 and 100, which helps gauge the probability of a financial crisis. Here's a breakdown of how it works:
### 1. **Market Volatility (VIX)**
- **How it's measured:**
- Uses the VIX index, which represents expected market volatility.
- Applies two exponential moving averages (EMAs) to smooth out the data—one fast and one slow.
- Triggers a signal if the fast EMA crosses above the slow EMA and VIX exceeds a defined threshold (default is 30).
- **Weighting:**
- Contributes up to 35% of the total risk score when active.
### 2. **Yield Curve Spread**
- **How it's measured:**
- Takes the difference between the yields of 10-year and 2-year U.S. Treasury bonds (inversion indicates recession risk).
- If the spread drops below a certain threshold (default is 0.2), it signals a potential recession.
- **Weighting:**
- Contributes up to 25% of the risk score.
### 3. **Stock Market Momentum**
- **How it's measured:**
- Analyzes the S&P 500 (SPY) using a 20-day EMA for price momentum.
- Checks for a cross under the 20-day EMA and if the 5-day rate of change (ROC) is less than -2.
- This combination signals bearish market momentum.
- **Weighting:**
- Contributes up to 20% of the risk score.
### 4. **Credit Risk (High Yield Spread)**
- **How it's measured:**
- Assesses high-yield corporate bond spreads using EMAs, similar to the VIX logic.
- A crossover of the fast EMA above the slow EMA combined with spreads exceeding a defined threshold (default is 5.0) indicates increased credit risk.
- **Weighting:**
- Contributes up to 20% of the total risk score.
### 5. **Risk Score Calculation**
- The final **risk score** ranges from 0 to 100 and is calculated using the weighted sum of the four indicators.
- The score is smoothed to minimize false signals and maintain stability.
### 6. **Risk Zones**
- **Extreme Risk:** If the risk score is ≥ 75, indicating a severe crisis warning.
- **High Risk:** If the risk score is between 15 and 75, signaling heightened risk.
- **Moderate Risk:** If the risk score is between 10 and 15, representing potential concerns.
- **Low Risk:** If the risk score is < 10, suggesting stable conditions.
### 7. **Visual & Alerts**
- The indicator plots the risk score on a chart with color-coded backgrounds to indicate risk levels: green (low), yellow (moderate), orange (high), and red (extreme).
- Alert conditions are set for each risk zone, notifying users when the risk level transitions into a higher zone.
This indicator aims to quickly detect potential financial crises by aggregating signals from key market factors, making it a versatile tool for traders, analysts, and risk managers.
Butterfly Harmonic Pattern [TradingFinder] Harmonic Detector🔵 Introduction
The Butterfly Harmonic Pattern is a sophisticated and highly regarded tool in technical analysis, utilized by traders to identify potential reversal points in the financial markets. This pattern is distinguished by its reliance on Fibonacci ratios and geometric configurations, which aid in predicting price movements with remarkable precision.
The origin of the Butterfly Harmonic Pattern can be traced back to the pioneering work of Bryce Gilmore, who is credited with discovering this pattern. Gilmore's extensive research and expertise in Fibonacci ratios laid the groundwork for the identification and application of this pattern in technical analysis.
The Butterfly pattern, like other harmonic patterns, is based on the principle that market movements are not random but follow specific structures and ratios.
The pattern is characterized by a distinct "M" shape in bullish scenarios and a "W" shape in bearish scenarios, each indicating a potential reversal point. These formations are identified by specific Fibonacci retracement and extension levels, making the Butterfly pattern a powerful tool for traders seeking to capitalize on market turning points.
The precise nature of the Butterfly pattern allows for the accurate prediction of target prices and the establishment of strategic entry and exit points, making it an indispensable component of a trader's analytical arsenal.
Bullish :
Bearish :
🔵 How to Use
Like other harmonic patterns, the Butterfly pattern is categorized based on how it forms at the end of an uptrend or downtrend. Unlike the Gartley and Bat patterns, the Butterfly pattern, similar to the Crab pattern, forms outside the wave 3 range at the end of a rally.
🟣 Types of Butterfly Harmonic Patterns
🟣 Bullish Butterfly Pattern
This pattern forms at the end of a downtrend and leads to a trend reversal from a downtrend to an uptrend.
🟣 Bearish Butterfly Pattern
In contrast to the Bullish Butterfly pattern, this pattern forms at the end of an uptrend and warns analysts of a trend reversal to a downtrend. In this case, traders are encouraged to shift their trading stance from buy trades to sell trades.
Advantages and Limitations of the Butterfly Pattern in Technical Analysis :
The Butterfly pattern is considered one of the precise and stable tools in financial market analysis. However, it is always important to pay special attention to the advantages and limitations of each pattern.
Here, we review the advantages and disadvantages of using the Butterfly harmonic pattern :
The main advantage of the Butterfly pattern is providing very accurate signals.
Using Fibonacci golden ratios and geometric rules, the Butterfly pattern identifies patterns accurately and systematically. (This high accuracy significantly helps investors in making trading decisions.)
Identifying this pattern requires expertise and experience in technical analysis.
Recognizing the Butterfly pattern might be complex for beginner traders. (Correct identification of the pattern necessitates mastery over geometric principles and Fibonacci ratios.)
The Butterfly harmonic pattern might issue false trading signals. (Traders usually combine the Butterfly pattern with other technical tools to confirm buy and sell signals.)
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
Scalper's Volatility Filter [QuantraSystems]Scalpers Volatility Filter
Introduction
The 𝒮𝒸𝒶𝓁𝓅𝑒𝓇'𝓈 𝒱𝑜𝓁𝒶𝓉𝒾𝓁𝒾𝓉𝓎 𝐹𝒾𝓁𝓉𝑒𝓇 (𝒮𝒱𝐹) is a sophisticated technical indicator, designed to increase the profitability of lower timeframe trading.
Due to the inherent decrease in the signal-to-noise ratio when trading on lower timeframes, it is critical to develop analysis methods to inform traders of the optimal market periods to trade - and more importantly, when you shouldn’t trade.
The 𝒮𝒱𝐹 uses a blend of volatility and momentum measurements, to signal the dominant market condition - trending or ranging.
Legend
The 𝒮𝒱𝐹 consists of a signal line that moves above and below a central zero line, serving as the indication of market regime.
When the signal line is positioned above zero, it indicates a period of elevated volatility. These periods are more profitable for trading, as an asset will experience larger price swings, and by design, trend-following indicators will give less false signals.
Conversely, when the signal line moves below zero, a low volatility or mean-reverting market regime dominates.
This distinction is critical for traders in order to align strategies with the prevailing market behaviors - leveraging trends in volatile markets and exercising caution or implementing mean-reversion systems in periods of lower volatility.
Case Study
Here we can see the indicator's unique edge in action.
Out of the four potential long entries seen on the chart - displayed via bar coloring, two would result in losses.
However, with the power of the 𝒮𝒱𝐹 a trader can effectively filter false signals by only entering momentum-trades when the signal line is above zero.
In this small sample of four trades, the 𝒮𝒱𝐹 increased the win rate from 50% to 100%
Methodology
The methodology behind the 𝒮𝒱𝐹 is based upon three components:
By calculating and contrasting two ATR’s, the immediate market momentum relative to the broader, established trend is calculated. The original method for this can be credited to the user @xinolia
A modified and smoothed ADX indicator is calculated to further assess the strength and sustainability of trends.
The ‘Linear Regression Dispersion’ measures price deviations from a fitted regression line, adding further confluence to the signals representation of market conditions.
Together, these components synthesize a robust, balanced view of market conditions, enabling traders to help align strategies with the prevailing market environment, in order to potentially increase expected value and win rates.
[blackcat] L2 Fibonacci BandsThe concept of the Fibonacci Bands indicator was described by Suri Dudella in his book "Trade Chart Patterns Like the Pros" (Section 8.3, page 149). These bands are derived from Fibonacci expansions based on a fixed moving average, and they display potential areas of support and resistance. Traders can utilize the Fibonacci Bands indicator to identify key price levels and anticipate potential reversals in the market.
To calculate the Fibonacci Bands indicator, three Keltner Channels are applied. These channels help in determining the upper and lower boundaries of the bands. The default Fibonacci expansion levels used are 1.618, 2.618, and 4.236. These levels act as reference points for traders to identify significant areas of support and resistance.
When analyzing the price action, traders can focus on the extreme Fibonacci Bands, which are the upper and lower boundaries of the bands. If prices trade outside of the bands for a few bars and then return inside, it may indicate a potential reversal. This pattern suggests that the price has temporarily deviated from its usual range and could be due for a correction.
To enhance the accuracy of the Fibonacci Bands indicator, traders often use multiple time frames. By aligning short-term signals with the larger time frame scenario, traders can gain a better understanding of the overall market trend. It is generally advised to trade in the direction of the larger time frame to increase the probability of success.
In addition to identifying potential reversals, traders can also use the Fibonacci Bands indicator to determine entry and exit points. Short-term support and resistance levels can be derived from the bands, providing valuable insights for trade decision-making. These levels act as reference points for placing stop-loss orders or taking profits.
Another useful tool for analyzing the trend is the slope of the midband, which is the middle line of the Fibonacci Bands indicator. The midband's slope can indicate the strength and direction of the trend. Traders can monitor the slope to gain insights into the market's momentum and make informed trading decisions.
The Fibonacci Bands indicator is based on the concept of Fibonacci levels, which are support or resistance levels calculated using the Fibonacci sequence. The Fibonacci sequence is a mathematical pattern that follows a specific formula. A central concept within the Fibonacci sequence is the Golden Ratio, represented by the numbers 1.618 and its inverse 0.618. These ratios have been found to occur frequently in nature, architecture, and art.
The Italian mathematician Leonardo Fibonacci (1170-1250) is credited with introducing the Fibonacci sequence to the Western world. Fibonacci noticed that certain ratios could be calculated and that these ratios correspond to "divine ratios" found in various aspects of life. Traders have adopted these ratios in technical analysis to identify potential areas of support and resistance in financial markets.
In conclusion, the Fibonacci Bands indicator is a powerful tool for traders to identify potential reversals, determine entry and exit points, and analyze the overall trend. By combining the Fibonacci Bands with other technical indicators and using multiple time frames, traders can enhance their trading strategies and make more informed decisions in the market.
Fisher+ [OSC]The Fisher Transform Indicator is classified as an oscillator, meaning that its value swings above and below a central point. This characteristic allows traders to identify overbought and oversold conditions, providing potential clues about market reversals. As mentioned previously, it is an oscillator so the strength of the move is displayed by how long the fisher line stays above/below zero. Indicator can be used to aid in confluence near supply/demand zones.
White Line = Fisher
Red/Blue Line = Moving Average
--Changes color whether fisher line is above/below the MA
Red/Blue Shaded Line = Moving Average
--Changes color based on a smoothing factor
Red/Blue Shaded Fill = Asset in Overbought/Oversold Conditions
Red/Blue Circles = Asset in Extreme Overbought/Oversold Conditions
Red/Blue Triangles = MACD Signals Below/Above "0"
Divergence Labels = Asset Signaling Divergence
The moving average line will turn red/blue as long as the fisher line is below/above the moving average. The shaded MA line will switch colors based on if it is moving in an up/down trend. The MA can also be used as a signal and treated similar to an oscillator. Market trending conditions will either keep the MA below/above the dashed zero line.
MACD code credited to LazyBear's MACD Leader indicator. It is used to filter out/confirm any signals such as divergences. As long as the MACD Leader line is above both the MACD line and signal lines then it'll signal with with a triangle. MACD divergences will be added at a later time.
SOLANA Performance & Volatility Analysis BB%Overview:
The script provides an in-depth analysis of Solana's performance and volatility. It showcases Solana's price, its inverse relationship, its own volatility, and even juxtaposes it against Bitcoin's 24-hour historical volatility. All of these are presented using the Bollinger Bands Percentage (BB%) methodology to normalise the price and volatility values between 0 and 1.
Key Components:
Inputs:
SOLANA PRICE (SOLUSD): The price of Solana.
SOLANA INVERSE (SOLUSDT.3S): The inverse of Solana's price.
SOLANA VOLATILITY (SOLUSDSHORTS): Volatility for Solana.
BITCOIN 24 HOUR HISTORICAL VOLATILITY (BVOL24H): Bitcoin's volatility over the past 24 hours.
BB Calculations:
The script uses the Bollinger Bands methodology to calculate the mean (SMA) and the standard deviation of the prices and volatilities over a certain period (default is 20 periods). The calculated upper and lower bands help in normalising the values to the range of 0 to 1.
Normalised Metrics Plotting:
For better visualisation and comparative analysis, the normalised values for:
Solana Price
Solana Inverse
Solana Volatility
Bitcoin 24hr Volatility
are plotted with steplines.
Band Plotting:
Bands are plotted at 20%, 40%, 60%, and 80% levels to serve as reference points. The area between the 40% and 60% bands is shaded to highlight the median region.
Colour Coding:
Different colours are used for easy differentiation:
Solana Price: Blue
Solana Inverse: Red
Solana Volatility: Green
Bitcoin 24hr Volatility: White
Licence & Creator:
The script adheres to the Mozilla Public Licence 2.0 and is credited to the author, "Volatility_Vibes".
Works well with Breaks and Retests with Volatility Stop
Feigenbaum ProjectionsThe theory of price delivery per Feigenbaum projections is credited to TRSTNGLRD, this indicator aims to aid traders from all backgrounds to utilize projections for determination of potential future price moves.
What follows is the simplest description of where to anchor the projection:
As price delivers and clears higher high (buy side liquidity) then reverses to clear most recent low (sell side liquidity), this becomes the anchorage point for the Feigenbaum projection and is referred to as perturbation. The start and end points for the projection should be only those candle bodies that wholly exist within the range within the high and low that were cleared by the perturbation, this range of candle bodies is to be considered the "initial condition". Structure that appears as a broadening formation is one such price delivery occurrence that can be utilized with these projections.
The projected zones are all pre-configured by TRSTNs specifications per Feigenbaum but can be adjusted if the need arises.
Price is expected to expand beyond the initial condition and into the negative and positive target zones, accuracy diminishes with further expansion and reevaluation should occur when a new perturbation is discovered.
It's recommended to explore various timeframes to find a perturbation by which to anchor the next Feigenbaum projection.
I'll do my best to update this description with time as more discoveries are made and TRSTNGLRD provides more guidance and feedback on this indicator.
Pythagorean Moving Averages (and more)When you think of the question "take the mean of this dataset", you'd normally think of using the arithmetic mean because usually the norm is equal to 1; however, there are an infinite number of other types of means depending on the function norm (p).
Pythagoras' is credited for the main types of means: his harmonic mean, his geometric mean, and his arithmetic mean:
Harmonic Average (p = -1):
- Take the reciprocal of all the numbers in the dataset, add them all together, divide by the amount of numbers added together, then take the reciprocal of the final answer.
Geometric Average (p = 0):
- Multiply all the numbers in the dataset, then take the nth root where n is equal to the amount of number you multiplied together.
Arithmetic Mean (p = 1):
- Add all the numbers in the dataset, then divide by the amount of numbers you added by.
A couple other means included in this script were the quadratic mean (p = 2) and the cubic mean (p = 3).
Quadratic Mean (p = 2):
- Square every number in the dataset, then divide by the amount of numbers your added by, then take the square root.
Cubic Mean (p = 3):
- Cube every number in the dataset, then divide by the amount of numbers you added by, then take the cube root.
There are an infinite number of means for every scenario of p, but they begin to follow a pattern after p = 3.
Read more:
www.cs.uni.edu
en.wikipedia.org
en.wikipedia.org
Note : I added the functions for the quadratic mean and cubic mean, but since market charts don't have those types of graphs, the functions don't usually work. It's the same reason why sometimes you'll see the harmonic average not working.
Disclaimer : This is not financial or mathematical advice, please look for someone certified before making any decisions.
VP and POCThis code is credited to juliangonzaconde. Have taken his help to modify his beautiful creation.
Volume profile is a key study when comes to understanding the auction trading process. Volume Profiles will show you exactly how much volume, as well as relative volume, occurred at each price as well as the exact number of contracts for the entire session. It is a visualization tool to understand the high activity zone and low activity zone.
Volume profile measures the confidence of the traders in the market. From short term trading perspective monitoring the developing volume profile in realtime make more sense to track current market participation behavior to take better trading decisions.
Hope this helps you in trading on daily timeframe.
Happy Trading.
