Bloomberg Financial Conditions Index (Proxy)The Bloomberg Financial Conditions Index (BFCI): A Proxy Implementation
Financial conditions indices (FCIs) have become essential tools for economists, policymakers, and market participants seeking to quantify and monitor the overall state of financial markets. Among these measures, the Bloomberg Financial Conditions Index (BFCI) has emerged as a particularly influential metric. Originally developed by Bloomberg L.P., the BFCI provides a comprehensive assessment of stress or ease in financial markets by aggregating various market-based indicators into a single, standardized value (Hatzius et al., 2010).
The original Bloomberg Financial Conditions Index synthesizes approximately 50 different financial market variables, including money market indicators, bond market spreads, equity market valuations, and volatility measures. These variables are normalized using a Z-score methodology, weighted according to their relative importance to overall financial conditions, and then aggregated to produce a composite index (Carlson et al., 2014). The resulting measure is centered around zero, with positive values indicating accommodative financial conditions and negative values representing tighter conditions relative to historical norms.
As Angelopoulou et al. (2014) note, financial conditions indices like the BFCI serve as forward-looking indicators that can signal potential economic developments before they manifest in traditional macroeconomic data. Research by Adrian et al. (2019) demonstrates that deteriorating financial conditions, as measured by indices such as the BFCI, often precede economic downturns by several months, making these indices valuable tools for predicting changes in economic activity.
Proxy Implementation Approach
The implementation presented in this Pine Script indicator represents a proxy of the original Bloomberg Financial Conditions Index, attempting to capture its essential features while acknowledging several significant constraints. Most critically, while the original BFCI incorporates approximately 50 financial variables, this proxy version utilizes only six key market components due to data accessibility limitations within the TradingView platform.
These components include:
Equity market performance (using SPY as a proxy for S&P 500)
Bond market yields (using TLT as a proxy for 20+ year Treasury yields)
Credit spreads (using the ratio between LQD and HYG as a proxy for investment-grade to high-yield spreads)
Market volatility (using VIX directly)
Short-term liquidity conditions (using SHY relative to equity prices as a proxy)
Each component is transformed into a Z-score based on log returns, weighted according to approximated importance (with weights derived from literature on financial conditions indices by Brave and Butters, 2011), and aggregated into a composite measure.
Differences from the Original BFCI
The methodology employed in this proxy differs from the original BFCI in several important ways. First, the variable selection is necessarily limited compared to Bloomberg's comprehensive approach. Second, the proxy relies on ETFs and publicly available indices rather than direct market rates and spreads used in the original. Third, the weighting scheme, while informed by academic literature, is simplified compared to Bloomberg's proprietary methodology, which may employ more sophisticated statistical techniques such as principal component analysis (Kliesen et al., 2012).
These differences mean that while the proxy BFCI captures the general direction and magnitude of financial conditions, it may not perfectly replicate the precision or sensitivity of the original index. As Aramonte et al. (2013) suggest, simplified proxies of financial conditions indices typically capture broad movements in financial conditions but may miss nuanced shifts in specific market segments that more comprehensive indices detect.
Practical Applications and Limitations
Despite these limitations, research by Arregui et al. (2018) indicates that even simplified financial conditions indices constructed from a limited set of variables can provide valuable signals about market stress and future economic activity. The proxy BFCI implemented here still offers significant insight into the relative ease or tightness of financial conditions, particularly during periods of market stress when correlations among financial variables tend to increase (Rey, 2015).
In practical applications, users should interpret this proxy BFCI as a directional indicator rather than an exact replication of Bloomberg's proprietary index. When the index moves substantially into negative territory, it suggests deteriorating financial conditions that may precede economic weakness. Conversely, strongly positive readings indicate unusually accommodative financial conditions that might support economic expansion but potentially also signal excessive risk-taking behavior in markets (López-Salido et al., 2017).
The visual implementation employs a color gradient system that enhances interpretation, with blue representing neutral conditions, green indicating accommodative conditions, and red signaling tightening conditions—a design choice informed by research on optimal data visualization in financial contexts (Few, 2009).
References
Adrian, T., Boyarchenko, N. and Giannone, D. (2019) 'Vulnerable Growth', American Economic Review, 109(4), pp. 1263-1289.
Angelopoulou, E., Balfoussia, H. and Gibson, H. (2014) 'Building a financial conditions index for the euro area and selected euro area countries: what does it tell us about the crisis?', Economic Modelling, 38, pp. 392-403.
Aramonte, S., Rosen, S. and Schindler, J. (2013) 'Assessing and Combining Financial Conditions Indexes', Finance and Economics Discussion Series, Federal Reserve Board, Washington, D.C.
Arregui, N., Elekdag, S., Gelos, G., Lafarguette, R. and Seneviratne, D. (2018) 'Can Countries Manage Their Financial Conditions Amid Globalization?', IMF Working Paper No. 18/15.
Brave, S. and Butters, R. (2011) 'Monitoring financial stability: A financial conditions index approach', Economic Perspectives, Federal Reserve Bank of Chicago, 35(1), pp. 22-43.
Carlson, M., Lewis, K. and Nelson, W. (2014) 'Using policy intervention to identify financial stress', International Journal of Finance & Economics, 19(1), pp. 59-72.
Few, S. (2009) Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press, Oakland, CA.
Hatzius, J., Hooper, P., Mishkin, F., Schoenholtz, K. and Watson, M. (2010) 'Financial Conditions Indexes: A Fresh Look after the Financial Crisis', NBER Working Paper No. 16150.
Kliesen, K., Owyang, M. and Vermann, E. (2012) 'Disentangling Diverse Measures: A Survey of Financial Stress Indexes', Federal Reserve Bank of St. Louis Review, 94(5), pp. 369-397.
López-Salido, D., Stein, J. and Zakrajšek, E. (2017) 'Credit-Market Sentiment and the Business Cycle', The Quarterly Journal of Economics, 132(3), pp. 1373-1426.
Rey, H. (2015) 'Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence', NBER Working Paper No. 21162.
Análise Fundamentalista
Market sessionsMarket sessions on chart. I used some coding from a large code. I wanted to see the market sessions on chart once each session opens. i am going to look at adding in supply and demand zones. Hopefully this can be a nice add on to any chart.
Aggregated Perpetual Futures Open InterestPurpose
Aggregates perpetual futures open interest across Binance, Bybit, and OKX for the base currency of the asset loaded in your tradingview window.
How It Works
Symbol detection: The script grabs syminfo.basecurrency (e.g., “BTC”) from whatever market is on screen.
Ticker mapping: It constructs the three perp-OI feeds that TradingView publishes in the form EXCHANGE:USDT.P_OI
Data request: For each feed it fetches the full OHLC candle (request.security) on the chart’s timeframe. If a venue doesn’t list that perp, the request simply returns na.
Aggregation: The script adds the opens, highs, lows, and closes of all non-na feeds to produce a single aggregated OI candle.
General Notes
The status line shows each venue’s individual OI close.
Extended Altman Z-Score ModelThe Extended Altman Z-Score Model represents a significant advancement in financial analysis and risk assessment, building upon the foundational work of Altman (1968) while incorporating contemporary data analytics approaches as proposed by Fung (2023). This sophisticated model enhances the traditional bankruptcy prediction framework by integrating additional financial metrics and modern analytical techniques, offering a more comprehensive approach to identifying financially distressed companies.
The model's architecture is built upon two distinct yet complementary scoring systems. The traditional Altman Z-Score components form the foundation, including Working Capital to Total Assets (X1), which measures a company's short-term liquidity and operational efficiency. Retained Earnings to Total Assets (X2) provides insight into the company's historical profitability and reinvestment capacity. EBIT to Total Assets (X3) evaluates operational efficiency and earning power, while Market Value of Equity to Total Liabilities (X4) assesses market perception and leverage. Sales to Total Assets (X5) measures asset utilization efficiency.
These traditional components are enhanced by extended metrics introduced by Fung (2023), which provide additional layers of financial analysis. The Cash Ratio (X6) offers insights into immediate liquidity and financial flexibility. Asset Composition (X7) evaluates the quality and efficiency of asset utilization, particularly in working capital management. The Debt Ratio (X8) provides a comprehensive view of financial leverage and long-term solvency, while the Net Profit Margin (X9) measures overall profitability and operational efficiency.
The scoring system employs a sophisticated formula that combines the traditional Z-Score with weighted additional metrics. The traditional Z-Score is calculated as 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5, while the extended components are weighted as follows: 0.5 * X6 + 0.3 * X7 - 0.4 * X8 + 0.6 * X9. This enhanced scoring mechanism provides a more nuanced assessment of a company's financial health, incorporating both traditional bankruptcy prediction metrics and modern financial analysis approaches.
The model categorizes companies into three distinct risk zones, each with specific implications for financial stability and required actions. The Safe Zone (Score > 3.0) indicates strong financial health, with low probability of financial distress and suitability for conservative investment strategies. The Grey Zone (Score between 1.8 and 3.0) suggests moderate risk, requiring careful monitoring and additional fundamental analysis. The Danger Zone (Score < 1.8) signals high risk of financial distress, necessitating immediate attention and potential risk mitigation strategies.
In practical application, the model requires systematic and regular monitoring. Users should track the Extended Score on a quarterly basis, monitoring changes in individual components and comparing results with industry benchmarks. Component analysis should be conducted separately, identifying specific areas of concern and tracking trends in individual metrics. The model's effectiveness is significantly enhanced when used in conjunction with other financial metrics and when considering industry-specific factors and macroeconomic conditions.
The technical implementation in Pine Script v6 provides real-time calculations of both traditional and extended scores, offering visual representation of risk zones, detailed component breakdowns, and warning signals for critical values. The indicator automatically updates with new financial data and provides clear visual cues for different risk levels, making it accessible to both technical and fundamental analysts.
However, as noted by Fung (2023), the model has certain limitations that users should consider. It may not fully account for industry-specific factors, requires regular updates of financial data, and should be used in conjunction with other analysis tools. The model's effectiveness can be enhanced by incorporating industry-specific benchmarks and considering macroeconomic factors that may affect financial performance.
References:
Altman, E.I. (1968) 'Financial ratios, discriminant analysis and the prediction of corporate bankruptcy', The Journal of Finance, 23(4), pp. 589-609.
Li, L., Wang, B., Wu, Y. and Yang, Q., 2020. Identifying poorly performing listed firms using data analytics. Journal of Business Research, 109, pp.1–12. doi.org
Global M2 Money Supply (USD) (27 currencies)M2 for 27 currencies, converted into USD.
Does not constitute 100% of global M2, but ~90% accounted for.
Leverages Dylan LeClair's starting point, adds to it.
COT NET SHG"This indicator evaluates market participants’ positioning through composite calculations based on the COT (Commitments of Traders) report from the CME. It aims to identify significant imbalances between buyers and sellers by highlighting moments when major market players concentrate unusually large volumes of contracts in either the long or short direction."
📊 Portfolio TrackerPortfolio Tracker
🧠 How This Script Works
This Pine Script generates a dynamic portfolio table in the upper-right corner of your chart. It:
Monitors your positions in: BTC, SOL, ADA, XRP, and XAU (Gold).
Calculates for each asset:
Current value,
Profit/Loss in your currency ,
Percentage change.
Color-coded output:
🟢 Green = Profit
🔴 Red = Loss
Automatically updates every few candles.
Tracks total portfolio value, PnL, and % return.
Triggers custom alerts when:
Total portfolio profit exceeds +5% or +10%.
🛠️ How to Customize It for Your Own Portfolio
🔹 1. Update your personal asset data
Inside the // === INPUTS === section of the code, modify these lines:
btc1_qty = 0.0013
btc1_entry = 72831.80
Repeat for each asset you own:
Replace xxx_qty with your amount.
Replace xxx_entry with your buy price (in your currency).
Make sure the request.security(...) line fetches the correct symbol.
🔹 2. Add more assets (optional)
Duplicate any block like ADA and change the variable names and symbols:
new_qty = ...
new_entry = ...
new_price = request.security("BINANCE:NEWTOKENUSD", timeframe.period, close)
Also include the new asset in:
total_pnl += ...
total_value_now += ...
total_cost += ...
The table.cell(...) block to show it in the table.
Why This Tool Rocks
Tracks all your holdings in one chart panel.
Requires no API or external data feed.
Real-time updates based on TradingView chart prices.
Fully editable and extendable to any other token or asset.
Previous week highs and lowsA script which marks a line pointing the highs and lows of the previous trading week.
Have a nice trade.
CANSLIM Từng Bước"CANSLIM Step-by-Step" Indicator Description for TradingView
CANSLIM Step-by-Step - Your Companion for Evaluating Stocks with the CANSLIM Methodology
Welcome, investors, to "CANSLIM Step-by-Step"! This indicator is designed to assist you in analyzing and evaluating stocks based on the seven core criteria of William J. O'Neil's renowned CANSLIM investment methodology.
Purpose of the Indicator:
This tool is not intended to provide fully automated buy/sell recommendations. Instead, it focuses on "digitizing" and visualizing each step in the CANSLIM evaluation process, helping you gain a more comprehensive and detailed overview of potential stocks.
Key Features:
Evaluation of 7 CANSLIM Criteria:
C (Current Quarterly Earnings): Allows manual input for the latest quarterly EPS growth (%) and positive EPS status. It also attempts to fetch data automatically (which may not be stable for all symbols) for comparison.
A (Annual Earnings & ROE): Prioritizes manual input for annual EPS growth rate (CAGR) and current ROE to ensure accuracy.
N (New Highs): Automatically analyzes price action from the chart to determine if the stock is near or making a new 52-week high.
S (Supply and Demand - Volume): Automatically analyzes current trading volume against its average to detect significant surges.
L (Leader or Laggard): You evaluate and input whether the stock is a market or industry leader.
I (Institutional Sponsorship): You evaluate and input the quality and quantity of significant institutional ownership.
M (Market Direction): Automatically analyzes the trend of a reference market index (e.g., VNINDEX) using moving averages.
Prioritized Manual Input for Financial Data: For criteria C and A, the indicator allows and encourages manual input to ensure the highest accuracy, given the inherent limitations of automatically accessing consistently updated financial data via Pine Script.
"Super Compact" Summary Table:
Clearly displays the status (Pass/Fail/N/A) of each criterion using color codes.
Provides specific values for each criterion (e.g., growth percentage, distance to 52-week high, volume ratio).
Aggregates a total score (out of 7) and a star rating (0 to 7 stars) for a quick overview of the stock's CANSLIM compliance.
Customizable Thresholds: You can adjust the evaluation thresholds for various criteria (e.g., minimum EPS growth %, minimum ROE %) to suit your risk appetite and personal standards.
How to Use Effectively:
Step 1: Select the stock symbol you wish to analyze.
Step 2: Open the indicator's settings:
Manually input your research findings for criteria C, A, L, and I.
Adjust thresholds and parameters for N, S, and M if needed.
Select the appropriate market index symbol for criterion M.
Step 3: Observe the summary table in the bottom-right corner of your screen for the overall assessment and detailed breakdown of each criterion.
"CANSLIM Step-by-Step" is a companion tool designed to help you systematize your stock evaluation process according to one of the most successful investment methodologies. Combine this indicator with your knowledge and experience to make informed investment decisions!
Commitment to Ongoing Development
We wish to share that the current "CANSLIM Step-by-Step" indicator is the initial version in our journey to build a more comprehensive CANSLIM stock evaluation support tool.
Our vision is to continuously develop and enhance this indicator with the following goals:
Increase Automation Capabilities: Explore solutions to automatically update certain basic financial data (for criteria C, A) more reliably and consistently, within the technical limits of Pine Script and available data sources.
Add Deeper Analytical Features: Such as visualizing changes in criteria over time, or comparisons with industry peers (where feasible).
Improve User Interface: Make data input and tracking even more intuitive and convenient.
Listen to and Integrate Community Feedback: We highly value all user feedback, bug reports, and feature suggestions to make "CANSLIM Step-by-Step" an increasingly useful tool.
This is a dedicated project, and we are committed to continually working to make "CANSLIM Step-by-Step" an even more powerful assistant for investors following the CANSLIM philosophy.
Swing Data - ADR% / RVol / PVol / Float % / Avg $ VolThis indicator provides a comprehensive table displaying essential swing trading metrics directly on your chart. Designed for traders who need a quick overview of stock volatility, liquidity, and volume dynamics at a glance.
Key Features:
✅ ADR% (Average Daily Range Percentage)
✅ Relative Volume (RVol)
✅ Projected Intraday Volume
✅ Average Daily $ Volume (AD NYSE:V )
✅ Float Percentage
✅ Market Capitalization
✅ LoD Distance (Low of Day distance in ATR%)
✅ Volume Buzz (current volume deviation from average)
✅ Sector & Industry classification
Customization Options:
➤ Table size (tiny to large)
➤ Adjustable position: Top-Left, Top-Right, Bottom-Left, Bottom-Right
➤ Dark Mode friendly colors
➤ Toggle each metric on/off
➤ Option to add a spacing row for clear visibility
Usage:
This script is ideal for intraday and swing traders who monitor volume surges, float dynamics, and volatility patterns to assess tradable setups. It combines key price and volume insights with fundamentals in one clean table — saving screen space while enhancing situational awareness.
Inspired by professional trading dashboards and adapted for TradingView charts.
Trend Overview & Percent Change with Growth per DayThis indicator helps to indentify the growth over a period. I would recommend using it on daily charts and to screen performance of an asset.
Bar ColorHis BTCUSDT Script to easy way in trade from next moving Guys due to the past levels spot and resistance and also where did price will break and push to upside,
key levels to watch
Take long hold in blue zone see our goal in long time with prefect entries
Like Pivot point
Resistance zone
Support levels
Breakout Points
Keep eye on these levels you may find details more in script
200W MA Extension ZonesThis indicator is specifically designed for analyzing Bitcoin on a 1-week chart. It plots the 200-week simple moving average (SMA) and visualizes key extension zones above it (50%, 100%, and 150%) to help assess long-term valuation extremes.
The zones are color-coded to highlight potential accumulation or distribution areas:
🟦 Very Cheap
🟩 Cheap
🟨 Fair Value
🟧 Expensive
🟥 Very Expensive
These visual bands help identify when Bitcoin may be significantly undervalued or overvalued relative to its long-term trend.
⚠️ Important: Use this indicator only on the weekly time frame (1W). Applying it to daily or intraday charts will not reflect the intended valuation model.
You can adjust the extension levels and shading transparency in the settings panel for personalized analysis.
FVG Candle HighlighterThis indicator highlights only the true Fair Value Gap (FVG) creator candle — the middle candle in a 3-bar FVG formation — with zero clutter.
🔹 Bullish FVG: Candle is colored if price gaps above the high two bars back
🔹 Bearish FVG: Candle is colored if price gaps below the low two bars back
✨ No boxes. No zones. Just pure, visual price-action accuracy.
🔧 Powered by Pine Script v6
🧠 Based on institutional-style FVG logic
🎯 Ideal for Smart Money / ICT / Order Block strategies
Coinbase Premium IndicatorPurpose
Indicates whether a crypto asset listed on a Coinbase spot market is trading at a premium or discount to other spot (Tether) markets.
How It Works
The script takes the base currency for the pair loaded in that TradingView window and searches for its Coinbase spot market. It also maps the base currency to the USDT (Tether) spot markets on Binance, Bybit, and OKX.
The Premium/ Discount is: (coin-btc-usd) - (sum(bnce-btc-usdt, bybt-btc-usdt, okx-btc-usdt))
General Notes
The status line of the Indicator displays the value of the premium/ discount and the market prices of the pair for each constituent exchange.
PER x RangeThis Pine Script calculates the target price of the Nikkei Average based on the EPS (Earnings Per Share) and different PER (Price-to-Earnings Ratio) multiples ranging from 17.5x to 12x, in increments of 0.5x. It then plots these target prices on the chart.
Key Features:
Input EPS: You can manually input the current EPS value of the Nikkei Average (the example uses 2380, but you can replace it with the actual EPS).
PER Multiples Calculation: The script calculates target prices for different PER multiples (17.5x, 17x, 16.5x, ..., down to 12x).
Plotting Target Prices: The calculated target prices (EPS * PER) are plotted on the chart as blue lines, showing you different target price scenarios based on varying PER multiples.
VOID Directional Spike MarkerThis indicator highlights significant directional moves on the $VOID chart (NYSE USI:UVOL − DERIBIT:DVOL ) using simple visual cues:
🔼 Green up arrows when the candle closes significantly higher than it opens
🔽 Red down arrows when the candle closes significantly lower than it opens
Threshold is fully customizable (default: 15,000,000)
Ideal for spotting explosive internal shifts on the 5-minute chart during key market moments
Alerts included for both up and down spikes
Use this to track aggressive buying or selling pressure across NYSE internals and time your entries on NQ, ES, or YM with stronger conviction.
Order Block with BoSHere’s a professional and concise description you can use for publishing your **TradingView script** titled **"Order Block with BoS"**:
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### 📌 **Description for TradingView Publication:**
**"Order Block with Break of Structure (BoS)"** is a powerful price action-based indicator designed to identify potential reversal zones and momentum shifts using **Order Block** detection combined with **Break of Structure (BoS)** confirmation.
### 🔍 **Key Features:**
* **Order Block Detection**: Highlights bullish and bearish order blocks using precise candle structure logic.
* **Break of Structure (BoS)**: Confirms structural breaks above swing highs or below swing lows to validate potential trend continuation or reversal.
* **Dynamic ATR Filter**: Uses a 14-period ATR with dynamic thresholds to confirm significant moves, filtering out weak breakouts.
* **Visual Aids**:
* Color-coded **boxes** to mark detected Order Blocks.
* **Arrows** at BoS confirmation points when ATR confirms strong momentum.
* Optional **dashed BoS lines** to show where price broke structure.
### ⚙️ **Customizable Inputs**:
* `Swing Length`: Defines the sensitivity of swing high/low detection.
* `Show Break of Structure`: Toggle on/off BoS confirmation lines.
* `Candle Lookback`: Number of historical candles to consider.
This indicator is ideal for traders who incorporate **smart money concepts**, **market structure analysis**, or **institutional order flow** strategies.
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Would you like me to help write the **strategy** version of this or translate the description into another language for international audiences?
Economic Event DatesThis TradingView indicator ("Economic Event Dates") plots significant economic event dates directly on your chart, helping you stay informed about potential market-moving announcements. It includes pre-configured dates for:
* **FOMC Meetings:** Key policy meetings of the Federal Open Market Committee.
* **CPI Releases:** Consumer Price Index data releases, a key measure of inflation.
* **Bitcoin Halvings:** Programmatic reductions in Bitcoin's new supply issuance.
**Features:**
* **Customizable Dates:** Easily input and manage dates for FOMC, CPI, and Halving events for current and future years (2025, 2026, and beyond for Halvings).
* **Visual Cues:** Displays vertical lines on the chart at the precise time of each event.
* **Event Labels:** Shows clear labels (e.g., "FOMC", "CPI", "Halving") for each event line.
* **Color Coding:** Distinct colors for FOMC (blue), CPI (orange), and Halving (purple) events for quick identification.
* **Future Events Focus:** Option to display only upcoming events relative to the current real time.
* **Morning Alerts:** (Optional) Triggers an alert on the morning of a scheduled event, providing a timely reminder.
* **Customizable Appearance:** Adjust line width and toggle label visibility.
**How to Use:**
1. Add the indicator to your TradingView chart.
2. Review and update the input dates for FOMC, CPI, and Halving events in the indicator settings. The script includes placeholders and notes for future dates that may require verification from official sources (e.g., federalreserve.gov, bls.gov).
3. Customize colors, line width, label visibility, and alert preferences as needed.
4. Observe the vertical lines on your chart indicating upcoming economic events.
This tool is designed for traders and investors who want to incorporate awareness of major economic events into their market analysis. Remember to verify future event dates as they are officially announced.
Created by YouNesta
QoQ PAT, Sales & OPM% Labels by GauravThis indicator automatically displays the Quarter-over-Quarter (QoQ) percentage change in Sales, PAT (Profit After Tax), and Operating Profit Margin (OPM%) directly on the price chart.
It fetches quarterly financial data using TradingView’s request.financial() function for:
Sales (TOTAL_REVENUE),
PAT (NET_INCOME),
Operating Profit (OPER_INCOME).
For each earnings update, it calculates:
Sales QoQ %: Growth in sales vs. the previous quarter,
PAT QoQ %: Growth in PAT vs. the previous quarter,
OPM %: Operating Profit Margin = (Operating Profit / Sales) × 100.
This helps traders and investors quickly visualize fundamental growth trends right alongside the candlestick chart, improving fundamental + technical analysis integration.
Long Short dom📊 Long Short dom (VI+) — Custom Vortex Trend Strength Indicator
This indicator is a refined version of the Vortex Indicator (VI) designed to help traders identify trend direction, momentum dominance, and potential long/short opportunities based on VI+ and VI– dynamics.
🔍 What It Shows:
• VI+ (Green Line): Measures upward trend strength.
• VI– (Red Line): Measures downward trend strength.
• Histogram (optional): Displays the difference between VI+ and VI–, helping visualize which side is dominant.
• Background Coloring: Highlights bullish or bearish dominance zones.
• Zero Line: A visual baseline to enhance clarity.
• Highest/Lowest Active Lines: Real-time markers for the strongest directional signals.
⸻
🛠️ Inputs:
• Length: Vortex calculation period (default 14).
• Show Histogram: Enable/disable VI+–VI– difference bars.
• Show Trend Background: Toggle colored zones showing trend dominance.
• Show Below Zero: Decide whether to display values that fall below 0 (for advanced use).
⸻
📈 Strategy Insights:
• When VI+ crosses above VI–, it indicates potential long momentum.
• When VI+ crosses below VI–, it signals possible short pressure.
• The delta histogram (VI+ – VI–) helps you quickly see shifts in momentum strength.
• The background shading provides an intuitive visual cue to assess trend dominance at a glance.
⸻
🚨 Built-in Alerts:
• Bullish Cross: VI+ crosses above VI– → possible entry long.
• Bearish Cross: VI+ crosses below VI– → possible entry short.
⸻
✅ Ideal For:
• Trend-following strategies
• Identifying long/short bias
• Confirming entries/exits with momentum analysis
⸻
This tool gives you clean, real-time visual insight into trend strength and shift dynamics, empowering smarter trade decisions with clarity and confidence.
Forex Session + Volume Profile [RunRox]📊 Forex Session + Volume Profile is built especially for traders who work with intra-session liquidity concepts or any strategy that needs a clear visual of trading sessions and the liquidity inside them.
Our team created this indicator to give you better session visibility, flexible session styling, and extra tools that help you navigate the market more easily.
📌 Features:
6 fully customizable sessions
Kill Zone (the high-impact trading window)
Volume Profile for each session
POC / VAL / VAH / LVN levels (Point of Control, Value Area Low, Value Area High, Low Volume Node)
PDH / PDL levels (Previous Day High / Low)
PWH / PWL levels (Previous Week High / Low)
NYM level (New York Market level)
Active sessions table
5 style options for each session
All of this gives you the flexibility to set up exactly the layout you need for your trading. Below, you’ll find a more detailed look at each feature.
🗓️ 6 CUSTOMIZABLE SESSION
The indicator includes six sessions that you can fully customize to fit your needs—everything from naming each session and choosing line colors to adjusting opacity, showing the volume profile, or even turning off a session entirely if you don’t need it.
Plus, you can pick different display styles for each session. As shown in the screenshot below, there are five style options you can apply individually to every session.
5 Style Options for Sessions
BOX
AREA
ZONES
LINES
CURVED
These styles can be customized for each session individually to help you highlight the sessions you care about on your chart. Example below
📢 VOLUME PROFILE
We’ve also integrated a Volume Profile into the indicator to pinpoint important levels on the chart. On top of that, we’ve added extra volume-based levels. Below, you’ll find the settings and a visual demo of how it appears on your chart.
To identify optimal entry points, you can use the following key reference levels:
POC (Point of Control)
VAL (Value Area Low)
VAH (Value Area High)
LVN (Low Volume Node)
You can also customize colors and line styles, or hide any levels you don’t need on your chart.
📐 ADDITIONAL LEVELS
You can display the following levels on your chart:
NYM (New York Market)
PDH (Previous Day High)
PDL (Previous Day Low)
PWH (Previous Week High)
PWL (Previous Week Low)
All of these are fully customizable with color selection and the option to extend lines into the next period.
💹 ACTIVE SESSION TABLE
The active sessions table helps you quickly identify the trading times for the sessions you care about. It’s fully customizable, with options to choose border and background colors for the table itself.
🟠 USAGE
This indicator is highly versatile: use it to simply mark trading sessions on your chart, set up the Kill Zone at your chosen time, or identify the context of the previous session by its most traded range levels. All of this makes the indicator an invaluable tool for any trader!
Divergence Macro Sentiment Indicator (DMSI)The Divergence Macro Sentiment Indicator (DMSI)
Think of DMSI as your daily “mood ring” for the markets. It boils down the tug-of-war between growth assets (S&P 500, copper, oil) and safe havens (gold, VIX) into one clear histogram—so you instantly know if the bulls have broad backing or are charging ahead with one foot tied behind.
🔍 What You’re Seeing
Green bars (above zero): Risk-on conviction.
Equities and commodities are rallying while gold and volatility retreat.
Red bars (below zero): Risk-off caution.
Gold or VIX are climbing even as stocks rise—or stocks aren’t fully joined by oil/copper.
Zero line: The line in the sand between “full-steam ahead” and “proceed with care.”
📈 How to Read It
Cross-Zero Signals
Bullish trigger: DMSI flips up through zero after a red stretch → fresh long entries.
Bearish trigger: DMSI tumbles below zero from green territory → tighten stops or go defensive.
Divergence Warnings
If SPX makes new highs but DMSI is rolling over (lower green bars or red), that’s your early red flag—rallies may fizzle.
Strength Confirmation
On pullbacks, only buy dips when DMSI ≥ 0. When DMSI is deeply positive, you can be more aggressive on position size or add leverage.
💡 Trade Guidance & Use Cases
Trend Filter: Only take your S&P or sector-ETF long setups when DMSI is non-negative—avoids hollow rallies.
Macro Pair Trades:
Deep red DMSI: go long gold or gold miners (GLD, GDX).
Strong green DMSI: lean into cyclicals, industrials, even energy names.
Risk Management:
Scale out as DMSI fades into negative territory mid-trade.
Scale in or add to winners when it stays bullish.
Swing Confirmation: Overlay on any oscillator or price-pattern system—accept signals only when the macro tide is flowing in your favour.
🚀 Why It Works
Markets don’t move in a vacuum. When stocks rally but the “real-economy” metals and volatility aren’t cooperating, something’s off under the hood. DMSI catches those cross-asset cracks before price alone can—and gives you an early warning system for smarter entries, tighter risk, and bigger gains when the macro trend really kicks in.
