AZRO Systems XRP Top/Bottom Indicator — Invite-Only (v1.0.3)AZRO Systems – XRP Top/Bottom Indicator — Invite-Only
VERSION v1.0.3 — first invite-only release
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WHAT IT DOES
• EARLY signal prints intra-bar when any of the multi-factor recipes is triggered.
• CONFIRMED signal prints after the weekly candle closes.
(If the Soft-Confirm filter is ON, a TOP must first pull back ≈30 % of ATR-90 before it can be confirmed.)
• Adds large green/red labels and a light bar-tint once confirmed.
• Historical testing shows materially lower draw-downs vs. passive holding while still capturing each macro upswing.
HOW IT WORKS (concept level – exact thresholds are locked)
1) Macro-Rotation Gauge – BTC-dominance extremes flag regime shifts that often precede alt-coin pivots.
2) Asset-Share Pivot – XRP market-cap share filters out false RSI spikes.
3) Momentum-Stress Check – Weekly RSI level plus an ATR-based pull-back filter captures exhaustion without waiting for close.
A label prints when any recipe combining these lenses meets its criteria, greatly reducing false signals versus single-factor scripts.
HOW TO USE
1) Chart: XRP-USD · 1-WEEK (lower time-frames unsupported)
2) Watch: Early label → light tint on Confirmed close
3) Alerts:
• Early Bottom / Early Top → ONCE PER BAR
• Confirmed Bottom / Confirmed Top → ONCE PER BAR CLOSE
USER-VISIBLE INPUTS
• Label distance (% ATR-90) – offset for label placement. (Default 50)
• Light-mode palette – swap colours for bright themes. (Default OFF)
• Soft-Confirm filter – ON waits for ≈30 % ATR pull-back on tops; OFF prints faster tops. (Default ON)
• Warning checkbox – visual reminder only; no effect on signals. (Default OFF)
ROAD-MAP
A BTC preset and an intraday scalp mode for XRP/BTC will be added to this same invite-only script — never separate listings.
LIMITATIONS & DISCLAIMER
• Designed only for the weekly timeframe; extreme events can override any model — always manage risk.
• Educational tool — not financial advice. Past performance ≠ future returns.
Analysis
Correlation MA – 15 Assets + Average (Optional)This indicator calculates the moving average of the correlation coefficient between your charted asset and up to 15 user-selected symbols. It helps identify uncorrelated or inversely correlated assets for diversification, pair trading, or hedging.
Features:
✅ Compare your current chart against up to 15 assets
✅ Toggle assets on/off individually
✅ Custom correlation and MA lengths
✅ Real-time average correlation line across enabled assets
✅ Horizontal lines at +1, 0, and -1 for easy visual reference
Ideal for:
Portfolio diversification analysis
Finding low-correlation stocks
Mean-reversion & pair trading setups
Crypto, equities, ETFs
To use: set the benchmark chart (e.g. TSLA), choose up to 15 assets, and adjust settings as needed. Look for assets with correlation near 0 or negative values for uncorrelated performance.
Blockchain Fundamentals: Global LiquidityGlobal Liquidity Indicator Overview
This indicator provides a comprehensive technical analysis of liquidity trends by deriving a Global Liquidity metric from multiple data sources. It applies a suite of technical indicators directly on this liquidity measure, rather than on price data. When this metric is expanding Bitcoin and crypto tends to bullish conditions.
Features:
1. Global Liquidity Calculation
Data Integration: Combines multiple market data sources using a ratio-based formula to produce a unique liquidity measure.
Custom Metric: This liquidity metric serves as the foundational input for further technical analysis.
2. Timeframe Customization
User-Selected Period: Users can select the data timeframe (default is 2 months) to ensure consistency and flexibility in analysis.
3. Additional Technical Indicators
RSI, Momentum, ROC, MACD, and Stochastic:
Each indicator is computed using the Global Liquidity series rather than price.
User-selectable toggles allow for enabling or disabling each individual indicator as desired.
4. Enhanced MACD Visualization
Dynamic Histogram Coloring:
The MACD histogram color adjusts dynamically: brighter hues indicate rising histogram values while darker hues indicate falling values.
When the histogram is above zero, green is used; when below zero, red is applied, offering immediate visual insight into momentum shifts.
Conclusion
This indicator is an enlightening tool for understanding liquidity dynamics, aiding in macroeconomic analysis and investment decision-making by highlighting shifts in liquidity conditions and market momentum.
Smart Trader Bot V0.5All-in-One Configurable Strategy – UT Bot + STC with Smart Position Management
This invite-only strategy combines proven indicators and unique filtering logic to offer a powerful, rules-based approach to trend trading. Designed for versatility across various markets and timeframes, it’s built to give traders full control over entries, exits, and risk logic.
⚙️ Core Logic
Primary Entry : UT Bot signal engine
Trend Confirmation : Schaff Trend Cycle (STC)
Optional Filters :
MA Cross (choose from 17 types)
Trend Breakout Filter
McGinley Dynamic Filter
🧩 Position Management Features
Stop Loss Options: ATR-based, Swing High/Low, Fixed %, Trailing SL
Take Profit Options: Fixed TP, Trailing TP with offset
Trade Flip Mode: Optional feature to auto-flip positions on opposite signals
Includes custom-built sideways-market detection logic
Suppresses unnecessary flips in ranging/choppy conditions
Designed to sustain win rate by avoiding premature trade reversals
🔧 Customization
17 selectable moving average types
Configurable signal logic and exit types
Adaptive SL/TP behavior across assets and timeframes
Compatible with crypto, forex, indices, and more
🧠 How It Works
Trade entries are based on UT Bot signals confirmed by STC trend logic
Optional confirmation from MA Cross, McGinley, or Trend Breakout logic
Once in position, SL/TP methods dynamically manage exits
Position flip logic enables trend continuation or reversal trading — enhanced by a unique sideways-market filter to limit noise in non-trending environments
🔍 Real-Time Strategy Configurations
Users granted access to this script can also view and use our shared TradingView charts configured across BTC, ETH, SOL, XRP, and more — on timeframes such as 1H, 30M, 15M, and 5M. These charts are live-linked and synced: any change in the strategy’s properties section will update instantly across all user views.
📌 Best Suited For
Traders who prefer rule-based, logic-driven automation
Scalpers and swing traders using TradingView alerts
Crypto, forex, and index market participants
Disclaimer: This is a closed-source strategy intended for experienced traders. No performance claims are made; past results are not indicative of future performance. Users are expected to evaluate and backtest strategy configurations to suit their own risk profile and market.
Access is provided for a limited evaluation period, during which users may review live chart configurations and strategy behavior in real time.
MVRV Ratio [Alpha Extract]The MVRV Ratio Indicator provides valuable insights into Bitcoin market cycles by tracking the relationship between market value and realized value. This powerful on-chain metric helps traders identify potential market tops and bottoms, offering clear buy and sell signals based on historical patterns of Bitcoin valuation.
🔶 CALCULATION The indicator processes MVRV ratio data through several analytical methods:
Raw MVRV Data: Collects MVRV data directly from INTOTHEBLOCK for Bitcoin
Optional Smoothing: Applies simple moving average (SMA) to reduce noise
Status Classification: Categorizes market conditions into four distinct states
Signal Generation: Produces trading signals based on MVRV thresholds
Price Estimation: Calculates estimated realized price (Current price / MVRV ratio)
Historical Context: Compares current values to historical extremes
Formula:
MVRV Ratio = Market Value / Realized Value
Smoothed MVRV = SMA(MVRV Ratio, Smoothing Length)
Estimated Realized Price = Current Price / MVRV Ratio
Distance to Top = ((3.5 / MVRV Ratio) - 1) * 100
Distance to Bottom = ((MVRV Ratio / 0.8) - 1) * 100
🔶 DETAILS Visual Features:
MVRV Plot: Color-coded line showing current MVRV value (red for overvalued, orange for moderately overvalued, blue for fair value, teal for undervalued)
Reference Levels: Horizontal lines indicating key MVRV thresholds (3.5, 2.5, 1.0, 0.8)
Zone Highlighting: Background color changes to highlight extreme market conditions (red for potentially overvalued, blue for potentially undervalued)
Information Table: Comprehensive dashboard showing current MVRV value, market status, trading signal, price information, and historical context
Interpretation:
MVRV ≥ 3.5: Potential market top, strong sell signal
MVRV ≥ 2.5: Overvalued market, consider selling
MVRV 1.5-2.5: Neutral market conditions
MVRV 1.0-1.5: Fair value, consider buying
MVRV < 1.0: Potential market bottom, strong buy signal
🔶 EXAMPLES
Market Top Identification: When MVRV ratio exceeds 3.5, the indicator signals potential market tops, highlighting periods where Bitcoin may be significantly overvalued.
Example: During bull market peaks, MVRV exceeding 3.5 has historically preceded major corrections, helping traders time their exits.
Bottom Detection: MVRV values below 1.0, especially approaching 0.8, have historically marked excellent buying opportunities.
Example: During bear market bottoms, MVRV falling below 1.0 has identified the most profitable entry points for long-term Bitcoin accumulation.
Tracking Market Cycles: The indicator provides a clear visualization of Bitcoin's market cycles from undervalued to overvalued states.
Example: Following the progression of MVRV from below 1.0 through fair value and eventually to overvalued territory helps traders position themselves appropriately throughout Bitcoin's market cycle.
Realized Price Support: The estimated realized price often acts as a significant
support/resistance level during market transitions.
Example: During corrections, price often finds support near the realized price level calculated by the indicator, providing potential entry points.
🔶 SETTINGS
Customization Options:
Smoothing: Toggle smoothing option and adjust smoothing length (1-50)
Table Display: Show/hide the information table
Table Position: Choose between top right, top left, bottom right, or bottom left positions
Visual Elements: All plots, lines, and background highlights can be customized for color and style
The MVRV Ratio Indicator provides traders with a powerful on-chain metric to identify potential market tops and bottoms in Bitcoin. By tracking the relationship between market value and realized value, this indicator helps identify periods of overvaluation and undervaluation, offering clear buy and sell signals based on historical patterns. The comprehensive information table delivers valuable context about current market conditions, helping traders make more informed decisions about market positioning throughout Bitcoin's cyclical patterns.
Swing Trading Strategy [TIAMATCRYPTO]**Overview:**
This Pine Script™ strategy is designed for swing trading, aiming to identify potential trend reversals or significant continuation points. It primarily uses fractal patterns as initial signals, which are then optionally confirmed and filtered by Liquidity Delta, Point of Control (POC), and an ADX trend strength indicator. The goal is to provide a configurable system that allows traders to tailor the entry conditions based on their preference for confirmation layers.
**How It Works - Core Logic & Indicator Synergy:**
The strategy's logic revolves around identifying high-probability swing points:
1. **Fractal Identification:**
* The base signals are generated by detecting **fractals**. A high fractal (potential swing high) is formed when a high is higher than a specified number (`fractalsCount`) of preceding and succeeding highs. Conversely, a low fractal (potential swing low) is formed when a low is lower than the surrounding lows.
* The `fractalRange` input is not directly used in the fractal detection logic provided in the script but is present as an input. (If it *was* intended for price range validation around fractals, this would need to be implemented).
2. **Liquidity Delta (Optional Confirmation):**
* If `useLiquidityDelta` is enabled, this indicator measures the net difference between buying and selling volume over a defined `ldPeriod`.
* **For Longs:** A positive Liquidity Delta (above `ldThreshold`) suggests stronger buying pressure, confirming a low fractal.
* **For Shorts:** A negative Liquidity Delta (below negative `ldThreshold`) suggests stronger selling pressure, confirming a high fractal.
* **Synergy:** Liquidity Delta helps gauge the conviction behind a fractal signal, filtering out fractals that occur on weak volume imbalances.
3. **Point of Control - POC (Optional Filter):**
* If `usePOC` is enabled, the strategy calculates the Point of Control (POC) – the price level with the highest traded volume over the `pocPeriod`. A `pocRangePercent` is used to define a zone around the POC.
* **For Longs:** The price should be above the `pocLowerRange` to consider a long entry, suggesting the price is finding support or has broken above a key volume area.
* **For Shorts:** The price should be below the `pocUpperRange` to consider a short entry, suggesting the price is facing resistance or has broken below a key volume area.
* **Synergy:** The POC acts as a dynamic support/resistance filter. Trading in alignment with the POC (e.g., buying above it, selling below it after a break) can improve trade quality by contextualizing price action within significant volume zones.
4. **ADX Filter (Optional Trend Strength Confirmation):**
* If `useADX` is enabled, the Average Directional Index (ADX) is used to filter trades based on trend strength.
* Trades are only considered if the `adxValue` is above the `adxThreshold`, indicating a trending market.
* **For Longs:** The Directional Indicator Plus (DI+) must be greater than DI-.
* **For Shorts:** The Directional Indicator Minus (DI-) must be greater than DI+.
* **Synergy:** The ADX filter helps avoid taking fractal signals during choppy or non-trending market conditions, focusing entries on periods where a directional move is more likely.
**Entry Conditions:**
* **Long Entry:**
1. A `lowFractal` is detected.
2. AND (if `useLiquidityDelta` is true) `liquidityDelta` > `ldThreshold`.
3. AND (if `usePOC` is true) `close` > `pocLowerRange`.
4. AND (if `useADX` is true) `adxValue` > `adxThreshold` AND `diPlusValue` > `diMinusValue`.
* **Short Entry:**
1. A `highFractal` is detected.
2. AND (if `useLiquidityDelta` is true) `liquidityDelta` < `-ldThreshold`.
3. AND (if `usePOC` is true) `close` < `pocUpperRange`.
4. AND (if `useADX` is true) `adxValue` > `adxThreshold` AND `diMinusValue` > `diPlusValue`.
**Exit Conditions:**
* **Stop Loss:** If `useStopLoss` is enabled, a percentage-based (`stopLossPercent`) stop loss is placed from the entry price.
* **Take Profit:** If `useTakeProfit` is enabled, a percentage-based (`takeProfitPercent`) take profit target is set from the entry price.
**Key Features & Customization:**
* **Backtest Date Range:** Specify start and end dates for backtesting.
* **Timeframe Selection:** Can run on the chart's timeframe or a user-specified one.
* **Fractal Settings:** `fractalsCount` (number of bars left/right to define a fractal).
* **Indicator Toggles:** Enable or disable Liquidity Delta, POC, and ADX filters individually.
* **Indicator Parameters:**
* `ldPeriod`, `ldThreshold` for Liquidity Delta.
* `pocPeriod`, `pocRangePercent` for Point of Control.
* `adxPeriod`, `adxThreshold` for ADX.
* **Risk Management:** Configurable `stopLossPercent` and `takeProfitPercent`.
**Strategy Properties & Backtesting Considerations (Important for Compliance):**
* **Default Properties (as per script `strategy()` call):**
* `Initial Capital`: 10,000
* `Default Quantity Type`: `strategy.percent_of_equity`
* `Default Quantity Value`: 10% (This means each trade risks 10% of equity if the stop loss is hit immediately at 100% of the position size, which is a common interpretation without more complex position sizing. **This is at the higher end of the 5-10% risk typically considered viable. Users should consider adjusting `default_qty_value` to a lower percentage (e.g., 1-2%) and then using the `stopLossPercent` to define the actual risk per trade to align with sustainable risk management practices.**)
* `Pyramiding`: 0 (No pyramiding allowed).
* **Commission and Slippage: CRITICAL FOR REALISTIC RESULTS**
* The script's `strategy()` call **does not** define default commission and slippage.
* **Users MUST manually set realistic `Commission` (e.g., 0.05% - 0.1% per trade) and `Slippage` (e.g., 1-2 ticks depending on the instrument and timeframe) in the strategy's "Properties" tab in TradingView.**
* Failing to set these will lead to overly optimistic backtest results that do not reflect real-world trading costs.
* **Sufficient Trades:** For the backtesting results to be statistically significant, aim for a dataset and settings that generate ideally more than 100 trades.
* **Date Range:** Utilize the `Backtest Start Date` and `Backtest End Date` inputs to test over relevant market periods.
* **Caution Warnings:** Do not publish if the strategy issues a caution warning in the Strategy Tester (e.g., "Strategy has an excessive number of entries...").
**Chart Visualization:**
* **Fractals:** High fractals are plotted as red triangles above the highs, and low fractals as green triangles below the lows.
* **Point of Control (POC):**
* The POC level is drawn as a solid purple line.
* The `pocUpperRange` and `pocLowerRange` are drawn as dashed purple lines.
* These lines are drawn for the most recent `pocPeriod` and update on the last bar.
* **Indicator Labels (on last bar):**
* If ADX is enabled: `ADX`, `DI+`, `DI-` values are labeled.
* If Liquidity Delta is enabled: The `LD` (normalized liquidity delta) value is labeled.
* **Performance Table:** A table in the bottom-right corner displays the `Net Profit` and `Win Rate (%)` of the strategy based on the backtest.
**Originality and Usefulness Justification:**
This strategy combines established concepts (Fractals, POC, ADX, Volume Analysis via Liquidity Delta) into a cohesive swing trading framework. The originality lies in:
1. The specific **combination and synergistic use** of these indicators, where each acts as a potential filter or confirmation for the others.
2. The **customizable nature**, allowing users to enable/disable layers of confirmation (Liquidity Delta, POC, ADX) to match their risk appetite and analysis style.
3. The Liquidity Delta calculation, while based on volume, provides a specific measure of buying vs. selling pressure to directly confirm fractal signals.
The purpose is not merely to merge indicators, but to create a structured decision-making process for swing trading, where fractal signals are qualified by volume dynamics, key volume-based price levels, and overall trend strength. This multi-faceted approach aims to improve the robustness of trading signals compared to using any single indicator in isolation.
**Disclaimer:**
This strategy is provided for educational and informational purposes only. Trading financial markets involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always conduct your own thorough research and backtesting, and consider your risk tolerance before making any trading decisions. Ensure you understand how commission and slippage impact results.
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**Key things addressed based on your warnings:**
* **Open-source reuse:** Assuming your code is original or properly credited if not. My description assumes originality.
* **Chart:** Explained what is plotted and why. The user publishing should ensure a clean chart.
* **Strategy results:**
* Emphasized the need to set realistic commission and slippage.
* Mentioned default account size and order size (and cautioned about the 10% risk).
* Advised on aiming for a sufficient number of trades.
* Explained default properties.
* Warned against publishing with caution warnings.
* **Originality and usefulness:** Provided a specific section justifying the combination of indicators and how they work together.
* **Description (general):** Made it detailed, explaining what the script does, how, and how to use its settings.
Remember to publish your script with a clean chart that clearly shows its outputs, and ensure your strategy settings in the publication match those you're describing or are using for any showcased backtest results.
TCT - Envelope MatrixTCT - Envelope Matrix
A powerful multi-envelope indicator that creates a comprehensive price channel system with 4 customizable envelopes and multiple intermediate levels for precise price action analysis.
Key Features:
• 4 customizable envelopes with adjustable percentages (0.2%, 0.4%, 0.6%, 0.8% by default)
• Optional EMA or SMA basis calculation
• Color-coded bands for easy visual identification
• Automatic horizontal lines showing current band values
• Midpoint lines between adjacent bands
• Additional 25%, 50%, and 75% levels between each band pair
The indicator provides:
- Clear visual representation of price channels
- Multiple support and resistance levels
- Dynamic price boundaries that adapt to market conditions
- Enhanced precision with intermediate levels between bands
Perfect for:
• Identifying potential support and resistance zones
• Spotting overbought/oversold conditions
• Finding potential reversal points
• Analyzing price volatility and channel width
• Making informed trading decisions based on price position relative to multiple bands
Customization Options:
• Adjustable length for the basis calculation
• Choice between EMA and SMA
• Customizable colors for each envelope
• Flexible percentage settings for each band
• Optional basis line color adjustment
This indicator is particularly useful for traders who want to analyze price action within multiple dynamic channels and identify potential trading opportunities based on price interactions with various support and resistance levels.
FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
ETF Builder & Backtest System [TradeDots]Create, analyze, and monitor your own custom “ETF-like” portfolio directly on TradingView. This script merges up to 10 different assets with user-defined weightings into a single composite chart, allowing you to see how your personalized portfolio would have performed historically. It is an original tool designed to help traders and investors quickly gauge risk and return profiles without leaving the TradingView platform.
📝 HOW IT WORKS
1. Custom Portfolio Construction
Multiple Assets : Combine up to 10 different stocks, ETFs, cryptocurrencies, or other symbols.
User-Defined Weights : Allocate each asset a percentage weight (e.g., 15% in AAPL, 10% in MSFT, etc.).
Single Composite Value : The script calculates a weighted “ETF-style” price, effectively simulating a merged portfolio curve on your chart.
2. Performance Tracking & Return Analysis
Automatic History Capture : The indicator records each asset’s starting price when it first appears in your chosen date range.
Rolling Updates : As time progresses, all asset prices are continually evaluated and the portfolio value is updated in real time.
Buy & Hold Returns : See how each asset—and the overall portfolio—performed from the “start” date to the most recent bar.
Annualized Return : Automatically calculates CAGR (Compound Annual Growth Rate) to help visualize performance over varying timescales.
3. Table & Visual Output
Performance Table : A comprehensive table displays individual asset returns, annualized returns, and portfolio totals.
Normalized Chart Plot : The composite ETF value is scaled to 100 at the start date, making it easy to compare relative growth or decline.
Optional Time Filter : You can define a specific date range (Start/End Dates) to focus on a particular period or to limit historical data.
⚙️ KEY FEATURES
1. Flexible Asset Selection
Choose any symbols from multiple asset classes. The script will only run calculations when data is available—no need to worry about missing quotes.
2. Dynamic Table Reporting
Start Price for each asset
Percentage Weight in the portfolio
Total Return (%) and Annualized Return (%)
3. Simple Backtesting Logic
This script takes a straightforward Buy & Hold perspective. Once the start date is reached, the portfolio remains static until the end date, so you can quickly assess hypothetical growth.
4. Plot Customization
Toggle the main “ETF” plot on/off.
Alter the visual style for tables and text.
Adjust the time filter to limit or extend your performance measurement window.
🚀 HOW TO USE IT
1. Add the Script
Search for “ETF Builder & Backtest System ” in the Indicators & Strategies tab or manually add it to your chart after saving it in your Pine Editor.
2. Configure Inputs
Enable Time Filter : Choose whether to restrict the analysis to a particular date range.
Start & End Date : Define the period you want to measure performance over (e.g., from 2019-12-31 to 2025-01-01).
Assets & Weights : Enter each symbol and specify a percentage weight (up to 10 assets).
Display Options : Pick where you want the Table to appear and choose background/text colors.
3. Interpret the Table & Plots
Asset Rows : Each asset’s ticker, weighting, start price, and performance metrics.
ETF Total Row : Summarizes total weighting, composite starting value, and overall returns.
Normalized Plot : Tracks growth/decline of the combined portfolio, starting at 100 on the chart.
4. Refine Your Strategy
Compare how different weights or a new mix of assets would have performed over the same period.
Assess if certain assets contribute disproportionately to your returns or volatility.
Use the results to guide allocations in your real trading or paper trading accounts.
❗️LIMITATIONS
1. Buy & Hold Only
This script does not handle rebalancing or partial divestments. Once the portfolio starts, weights remain fixed throughout the chosen timeframe.
2. No Reinvestment Tracking
Dividends or other distributions are not factored into performance.
3. Data Availability
If historical data for a particular asset is unavailable on TradingView, related results may display as “N/A.”
4. Market Regimes & Volatility
Past performance does not guarantee similar future behavior. Markets can change rapidly, which may render historical backtests less predictive over time.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The “ETF Builder & Backtest System ” is provided for informational and educational purposes only. It does not constitute financial advice.
Always conduct your own research.
Use proper risk management and position sizing.
Past performance does not guarantee future results.
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Use this indicator as part of a broader trading or investment approach—consider fundamental and technical factors, overall market context, and personal risk tolerance. No trading tool can assure profits; exercise caution and responsibility in all financial decisions.
PivotBox by Nadeem Al-QahwiPivotBox by Nadeem Al-Qahwi
General Idea of the Indicator: The PivotBox indicator is an advanced technical analysis tool designed to identify key reversal points in the market based on pivot highs and pivot lows. The indicator helps traders to detect breakout and breakdown opportunities based on past price movements, guiding informed trading decisions.
Indicator Functions:
Key Reversal Points (Pivot Points):
The indicator identifies pivot highs and pivot lows over a user-defined period, helping traders spot significant price levels in the market.
These points are plotted on the chart, showing where market reversals may occur.
Breakouts and Breakdowns:
The indicator identifies breakouts when the price moves above a pivot high or breakdowns when the price falls below a pivot low.
Once these breakouts or breakdowns are detected, the indicator draws lines indicating the critical price levels for visual reference.
Trend Levels using Zero-Lag MA:
The indicator includes an option to add a Zero-Lag Moving Average (Zero-Lag MA) to display the overall trend in the market. This moving average helps filter out noise and identify the general market direction, improving trade decision-making.
Line Styles:
The pivot points (highs and lows) are displayed using different line styles, such as solid, dashed, or dotted lines. The user can customize the style based on their preference.
These lines represent the breakouts or breakdown levels in the market.
Alerts:
The indicator can activate alerts when a breakout or breakdown occurs. Users can customize the alerts to notify them when specific conditions are met, ensuring that they do not miss significant price movements.
Input Variables:
Period (prd): The time period over which the pivot highs and lows are calculated. The user can define this period based on their trading strategy.
Max Breakout Length (bo_len): The maximum time duration for a breakout or breakdown to occur. This variable helps determine the relevance of the price movement.
Threshold Rate (cwidthu): The width percentage that helps to define the price area for breakouts and breakdowns.
Line Style (lstyle): Allows the user to choose the style of lines used to display the pivot points (solid, dashed, or dotted).
Minimum Number of Tests (mintest): The minimum number of tests required before a breakout or breakdown is considered valid.
How the Indicator Works:
The indicator first calculates the pivot highs and lows based on the user-defined period (Period).
It then tracks price movements to detect if a breakout or breakdown occurs.
When a breakout or breakdown is confirmed, the indicator draws lines at these levels and shows the user the new price direction.
Alerts can be triggered based on predefined conditions such as when a breakout or breakdown occurs.
The Zero-Lag MA helps the user visualize the trend, adding another layer of analysis to the market movements.
Key Benefits:
Accurate Reversal Point Analysis: Helps traders identify key entry and exit points based on precise technical analysis.
Breakout and Breakdown Detection: Allows traders to spot breakout and breakdown opportunities in real-time.
Customizable Alerts: Users can set up alerts to notify them when a breakout or breakdown happens, ensuring they don't miss important market moves.
Flexible Customization: The indicator offers various options to customize the display (line styles, alerts, trendlines), catering to different trading strategies.
Custom Performance TableThis script generates a table designed to provide a concise yet highly customizable overview of the performance of multiple financial instruments, displayed directly on the chart. The table can include up to 40 tickers, each individually configurable, with values updated in real time based on either the current chart timeframe or a specific user-selected timeframe.
NOTE : The update frequency of the table values depends on the refresh rate of the chart's main ticker to which the indicator is applied. To ensure a consistent and reliable data feed, especially when monitoring heterogeneous instruments, it is recommended to apply the indicator to a highly liquid and continuously traded asset, such as BTCUSD.
PERFORMANCE CALCULATION MODES
You can choose from three different performance calculation modes:
1) Change % (Percentage Change)
Displays the percentage change of the current price compared to the previous candle within the selected timeframe.
(Current Price - Previous Price) / Previous Price * 100
This mode provides an immediate and straightforward measure of each instrument's percentage movement, useful for quick visual comparisons of relative strength among assets.
2) Z-Score
The Z-Score measures how much the current price variation deviates from the historical average variation, relative to the standard deviation of those variations.
(Current Variation - Average Variation) / Standard Deviation of Variations
The result indicates how statistically unusual a movement is:
- Values near 0 suggest normal variations.
- Values above ±2 indicate statistically significant deviations.
This is a valuable tool for identifying overbought/oversold conditions or market stress events and is often used in mean reversion strategies.
NOTE : Due to technical constraints, Z-Score can only be calculated when the selected timeframe matches the chart's timeframe exactly.
3) RAROC (Risk-Adjusted Return on Capital)
RAROC expresses an asset's performance in relation to the risk taken, measured through its volatility (standard deviation of price).
Percentage Change / Standard Deviation of Price
It allows for an assessment of return efficiency in relation to volatility.
A high RAROC value indicates a high return relative to the risk, making it a useful tool for comparing assets with different risk profiles. It is especially suitable for portfolio selection and allocation purposes.
TABLE CONFIGURATION
Each ticker can be customized with its own label, colors, and position in the table.
Each row can display the ticker name or a custom label, which, at the user's discretion, can either replace the name or be shown as an informational tooltip.
The table can be placed anywhere on the chart using horizontal and vertical offset parameters. Thanks to offset support, you can, for example, create financial market overview layouts. This can be done by completely “cleaning” the chart from price and indicators using TradingView settings, and then displaying multiple tables simultaneously (see the example chart published here).
Advanced customization options are also available for the table's appearance, including font settings, colors, borders, and more.
CALCULATION TIMEFRAME
The indicator allows the user to force a specific timeframe (Daily, Weekly, Monthly, Yearly) when applied to intraday charts.
However, for Z-Score mode, the selected timeframe must match the chart's timeframe exactly to ensure correct computation. Otherwise, the script will halt until settings are properly adjusted.
USAGE NOTES
Custom Performance Table is a flexible and adaptable tool, suitable for both intraday operations and medium- to long-term analysis. It is designed for traders and analysts who need to compare assets based on quantitative metrics, whether simple (like percentage change) or more advanced and risk-adjusted (such as Z-Score and RAROC).
Triad Macro Gauge__________________________________________________________________________________
Introduction
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The Triad Macro Gauge (TMG) is designed to provide traders with a comprehensive view of the macroeconomic environment impacting financial markets. By synthesizing three critical market signals— VIX (volatility) , Credit Spreads (credit risk) , and the Stocks/Bonds Ratio (SPY/TLT) —this indicator offers a probabilistic assessment of market sentiment, helping traders identify bullish or bearish macro conditions.
Holistic Macro Analysis: Combines three distinct macroeconomic indicators for multi-dimensional insights.
Customization & Flexibility: Adjust weights, thresholds, lookback periods, and visualization styles.
Visual Clarity: Dynamic table, color-coded plots, and anomaly markers for quick interpretation.
Fully Consistent Scores: Identical values across all timeframes (4H, daily, weekly).
Actionable Signals: Clear bull/bear thresholds and volatility spike detection.
Optimized for timeframes ranging from 4 hour to 1 week , the TMG equips swing traders and long-term investors with a robust tool to navigate macroeconomic trends.
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Key Indicators
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VIX (CBOE:VIX): Measures market volatility (negatively weighted for bearish signals).
Credit Spreads (FRED:BAMLH0A0HYM2EY): Tracks high-yield bond spreads (negatively weighted).
Stocks/Bonds Ratio (SPY/TLT): Evaluates equity sentiment relative to treasuries (positively weighted).
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Originality and Purpose
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The TMG stands out by combining VIX, Credit Spreads, and SPY/TLT into a single, cohesive indicator. Its unique strength lies in its fully consistent scores across all timeframes, a critical feature for multi-timeframe analysis.
Purpose: To empower traders with a clear, actionable tool to:
Assess macro conditions
Spot market extremes
Anticipate reversals
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How It Works
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VIX Z-Score: Measures volatility deviations (inverted for bearish signals).
Credit Z-Score: Tracks credit spread deviations (inverted for bearish signals).
Ratio Z-Score: Assesses SPY/TLT strength (positively weighted for bullish signals).
TMG Score: Weighted composite of z-scores (bullish > +0.30, bearish < -0.30).
Anomaly Detection: Identifies extreme volatility spikes (z-score > 3.0).
All calculations are performed using daily data, ensuring that scores remain consistent across all chart timeframes.
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Visualization & Interpretation
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The script visualizes data through:
A dynamic table displaying TMG Score , VIX Z, Credit Z, Ratio Z, and Anomaly status, with color gradients (green for positive, red for negative, gray for neutral/N/A).
A plotted TMG Score in Area, Histogram, or Line mode , with adaptive opacity for clarity.
Bull/Bear thresholds as horizontal lines (+0.30/-0.30) to signal market conditions.
Anomaly markers (orange circles) for volatility spikes.
Crossover signals (triangles) for bull/bear threshold crossings.
The table provides an immediate snapshot of macro conditions, while the plot offers a visual trend analysis. All values are consistent across timeframes, simplifying multi-timeframe analysis.
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Script Parameters
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Extensive customization options:
Symbol Selection: Customize VIX, Credit Spreads, SPY, TLT symbols
Core Parameters: Adjust lookback periods, weights, smoothing
Anomaly Detection: Enable/disable with custom thresholds
Visual Style: Choose display modes and colors
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Conclusion
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The Triad Macro Gauge by Ox_kali is a cutting-edge tool for analyzing macroeconomic trends. By integrating VIX, Credit Spreads, and SPY/TLT, TMG provides traders with a clear, consistent, and actionable gauge of market sentiment.
Recommended for: Swing traders and long-term investors seeking to navigate macro-driven markets.
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Credit & Inspiration
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Special thanks to Caleb Franzen for his pioneering work on macroeconomic indicator blends – his research directly inspired the core framework of this tool.
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Notes & Disclaimer
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This is the initial public release (v2.5.9). Future updates may include additional features based on user feedback.
Please note that the Triad Macro Gauge is not a guarantee of future market performance and should be used with proper risk management. Past performance is not indicative of future results.
Trading Session Highs and LowsTrading Session Highs and Lows
This script provides an intuitive way to visualize key market levels from major trading sessions: Asia, London, New York, and New York Close. By automatically plotting the high and low of each session, it helps traders quickly identify important price levels that could impact market behavior.
Features include:
Session Marking: The script marks the high and low for each major session (Asia, London, New York, and New York Close).
Customizable Lines and Labels: You can adjust the line style, width, and color for each session’s high/low markers. The session name (e.g., "London", "New York") and the PDH/PDL (Prior Day High and Low) are also shown to give clear context.
Real-Time Updates: The levels are updated in real-time to reflect the current price action, helping you gauge price movement throughout the trading day.
Customizable Indicators: Easily adjust the visibility of the different sessions and the labels to focus on the session that matters most to your trading strategy.
This tool is designed to help day traders spot important levels for potential breakouts or reversals, making it easier to base your trading decisions on well-established price points. Ideal for scalpers, swing traders, and anyone who trades across multiple sessions.
Institutional MACD (Z-Score Edition) [VolumeVigilante]📈 Institutional MACD (Z-Score Edition) — Professional-Grade Momentum Signal
This is not your average MACD .
The Institutional MACD (Z-Score Edition) is a statistically enhanced momentum tool, purpose-built for serious traders and breakout hunters . By applying Z-Score normalization to the classic MACD structure, this indicator uncovers statistically significant momentum shifts , enabling cleaner reads on price extremes, trend continuation, and potential reversals.
💡 Why It Matters
The classic MACD is powerful — but raw momentum values can be noisy and relative , especially on volatile assets like BTC/USD . By transforming the MACD line, signal line, and histogram into Z-scores , we anchor these signals in statistical context . This makes the Institutional MACD:
✔️ Timeframe-agnostic and asset-normalized
✔️ Ideal for spotting true breakouts , not false flags
✔️ A reliable tool for detecting momentum divergence and exhaustion
🧪 Key Features
✅ Full Z-Score normalization (MACD, Signal, Histogram)
✅ Highlighted ±Z threshold bands for overbought/oversold zones
✅ Customizable histogram coloring for visual momentum shifts
✅ Built-in alerts for zero-crosses and Z-threshold breaks
✅ Clean overlay with optional display toggles
🔁 Strategy Tip: Mean Reversion Signals with Statistical Confidence
This indicator isn't just for spotting breakouts — it also shines as a mean reversion tool , thanks to its Z-Score normalization .
When the Z-Score histogram crosses beyond ±2, it marks a statistically significant deviation from the mean — often signaling that momentum is overstretched and the asset may be due for a pullback or reversal .
📌 How to use it:
Z > +2 → Price action is in overbought territory. Watch for exhaustion or short setups.
Z < -2 → Momentum is deeply oversold. Look for reversal confirmation or long opportunities.
These zones often precede snap-back moves , especially in range-bound or corrective markets .
🎯 Combine Z-Score extremes with:
Candlestick confirmation
Support/resistance zones
Volume or price divergence
Other mean reversion tools (e.g., RSI, Bollinger Bands)
Unlike the raw MACD, this version delivers statistical thresholds , not guesswork — helping traders make decisions rooted in probability, not emotion.
📢 Trade Smart. Trade Vigilantly.
Published by VolumeVigilante
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
7-Channel Trend Meter v3🔥 7-Channel Trend Meter – Ultimate Trend Confirmation Tool 💹
Purpose: Supplementary indicator used as confirmation
The 7-Channel Trend Meter offers an all-in-one confirmation system that combines 7 high-accuracy indicators into one easy-to-read visual tool. Say goodbye to guesswork and unnecessary tab-switching—just clear, actionable signals for smarter trades. Whether you're trading stocks, crypto, or forex, this indicator streamlines your decision-making process and enhances your strategy’s performance.
⚙️ What’s Inside The Box?
Here is each tool that the Trend Meter uses, and why/how they're used:
Average Directional Index: Confirms market strength ✅
Directional Movement Index: Confirms trend direction ✅
EMA Cross: Confirms reversals in trend through average price ✅
Relative Strength Index: Confirms trend through divergences ✅
Stochastic Oscillator: Confirms shifts in momentum ✅
Supertrend: Confirms trend-following using ATR calculations ✅
Volume Delta: Confirms buying/selling pressure weight by finding differences ✅
🧾 How To Read It:
🟨 Bar 1 – Market Strength Meter:
Light Gold 🟡: Strong market with trending conditions.
Dark Gold 🟤: Weakening market or consolidation—proceed with caution.
📊 Bars 2 to 7 – Trend Direction Confirmations:
🟩 Green: Bullish signal, uptrend likely.
🟥 Red: Bearish signal, downtrend likely.
💯 Why it's helpful to traders:
✅ 7 Confirmations in 1 View: No need to flip between multiple charts.
✅ Visual Clarity: Spot trends instantly with a quick glance.
✅ Perfect for Entry Confirmation: Confirm trade signals before pulling the trigger.
✅ Boosts Your Win Rate: Make data-backed decisions, not guesses.
✅ Works Across Multiple Markets: Stocks, crypto, forex—you name it 🌍.
🤔 "What's with the indicator mashup/How do these components work together? 🤔
The 7-Channel Trend Meter is designed as an original and useful tool that integrates multiple indicators to enhance trading decisions, rather than merely combining existing tools without logical coherence. This strategic mashup creates a comprehensive analysis framework that offers deeper insights into market conditions by capitalizing on each component's unique strengths. The careful integration of seven indicators creates a unified system that eliminates conflicting signals and enhances the decision-making process. Rather than simply merging indicators for the sake of it, the 7-Channel Trend Meter is designed to streamline trading strategies, making it a practical tool for traders across various markets. By leveraging the combined strengths of these indicators, traders can act with greater confidence, backed by comprehensive data rather than fragmented insights. Here’s how they synergistically work together:
Average Directional Index (ADX) and Directional Movement Index (DMI): The reason for this mashup is because ADX indicates the strength of the prevailing trend, while the DMI pinpoints its direction. Together, they equip traders with a dual framework that not only identifies whether to engage with a trend but also quantifies its strength, allowing for more decisive trading strategies.
EMA Cross: The reason for this addition to the mashup is because this tool signals potential trend reversals by identifying moving average crossovers. When combined with the ADX and DMI, traders can better differentiate between genuine trend shifts and market noise, leading to more accurate entries.
Relative Strength Index (RSI) and Stochastic Oscillator: The reason for this mashup is because by using both momentum indicators, traders gain a multifaceted view of market dynamics. The RSI assesses overbought or oversold conditions, while the Stochastic Oscillator confirms momentum shifts. When both agree with the trend signals from the DMI, it enhances the reliability of reversal or continuation strategies.
Supertrend: The reason for this addition to the mashup is because as a trailing stop based on market volatility, the Supertrend indicator works hand-in-hand with the ADX’s strength assessment, allowing traders to ride strong trends while managing risk. This cohesion prevents premature exits during minor pullbacks.
Volume Delta: The reason for this addition to the mashup is because integrating volume analysis helps validate signals from the price action indicators. Significant volume behind a price movement reinforces the likelihood of its continuation, ensuring that traders can act on well-supported signals.
🔍 How it does what it says it does 🔍
While the exact calculations remain proprietary, the following outlines how the components synergistically work to aid traders in making informed decisions:
Market Strength Assessment: Average Directional Index (ADX)
This component is used as confirmation by measuring the strength of the market trend on a scale from 0 to 100. A reading above 20 generally indicates a strong trend, while readings below 20 suggest sideways movement. The Trend Meter flags strong trends, effectively helping traders identify optimal conditions for entering positions.
Trend Direction Confirmation: Directional Movement Index (DMI)
This component is used as confirmation by distinguishing between bullish and bearish trends by evaluating price movements. This combination allows traders to confirm not only if a trend exists but also its direction, informing whether to buy or sell.
Trend Reversal Detection: Exponential Moving Average (EMA) Cross
This component is used as confirmation by calculating two EMAs (one shorter and one longer) to identify potential reversal points. When the shorter EMA crosses above the longer EMA, it signals a bullish reversal, and vice versa for bearish reversals. This helps traders pinpoint optimal entry or exit points.
Momentum Analysis: Relative Strength Index (RSI) and Stochastic Oscillator
These components are used as confirmation by providing insights into momentum. The RSI assesses the speed and change of price movements, indicating overbought or oversold conditions. The Stochastic Oscillator compares a particular closing price to a range of prices over a specified period. This helps identify whether momentum is slowing or speeding up, offering a clear view of potential reversal points. When both the RSI and Stochastic Oscillator converge on signals, it increases the reliability of those signals in trading decisions.
Volatility-Based Trend Following: Supertrend
This component is used as confirmation by utilizing Average True Range (ATR) calculations to help traders stay in momentum-driven trades by providing dynamic support and resistance levels that adapt to volatility. This enables better risk management while allowing traders to capture stronger trends.
Volume Confirmation: Volume Delta
This component is used as confirmation by analyzing buying and selling pressure by measuring the difference between buy and sell volumes, offering critical insights into market sentiment. Significant volume behind a price movement increases confidence in the sustainability of that move.
🧠 Pro Tip:
When all 7 bars line up in green or red, it’s time to take action: load up for a confirmed move or sit back and wait for market confirmation. Let the Trend Meter guide your strategy with precision.
Conclusion:
Integrate the 7-Channel Trend Meter as useful confirmation for your TradingView strategy and stop trading like the average retail trader. This tool eliminates the noise and helps you stay focused on high-confidence trades.
Daily Movement AnalysisDaily Volatility Explorer: 7-Day Market Pulse Indicator
Unlock the hidden rhythms of market movements with this powerful analytical tool designed for both traditional and crypto traders. This indicator meticulously tracks and analyzes price volatility patterns across all seven days of the week, giving you a strategic edge in planning your trades.
🎯 Key Features:
• Dynamic 3-month rolling analysis of daily price movements
• Real-time volatility comparison across all trading days
• Clear visual representation through color-coded bar charts
• Detailed statistical table with exact pip movements
• Sample size tracking for statistical reliability
• Works seamlessly on both traditional and crypto markets
💡 Why Traders Need This:
1. Optimal Trade Timing
- Identify the most volatile trading days for maximum opportunity
- Discover the quietest days to avoid choppy markets
- Perfect for swing traders and day traders alike
2. Risk Management Enhancement
- Set smarter stop-losses based on typical daily ranges
- Adjust position sizes according to daily volatility patterns
- Avoid overtrading during historically low-volatility periods
3. Strategic Planning
- Plan your trading week around peak volatility days
- Optimize entry and exit points based on historical movements
- Better time management by focusing on the most active days
4. Market Psychology Insights
- Understand weekly market rhythm and institutional patterns
- Identify how weekend gaps affect crypto markets
- Spot changes in market behavior across different days
🔍 Perfect For:
• Forex traders tracking major currency pairs
• Crypto traders navigating 24/7 markets
• Gold and commodity traders
• Day traders optimizing their trading schedule
• Swing traders planning optimal entry/exit days
📊 Data-Driven Decisions:
The indicator maintains a rolling 3-month window of data, providing fresh, relevant insights while filtering out outdated patterns. Each day's analysis is based on actual market movements, giving you reliable, actionable intelligence for your trading decisions.
⚡ Pro Tip: Use this indicator alongside your existing strategy to enhance your trading plan and improve your timing. The color-coded visual system makes it easy to spot patterns at a glance, while the detailed statistics table provides the hard numbers you need for precise planning.
Remember: Markets evolve, and this indicator helps you stay on top of changing patterns in real-time. Whether you're trading traditional markets or crypto, understanding daily volatility patterns is crucial for consistent trading success.
Backtesting Stats (Altrady)Track and analyze your backtesting results directly on your chart.
This indicator simplifies manual backtesting by summarizing your trades in a clear, structured table. Enter your R-values (one per line) in the text area, and instantly see:
✅ Trade list – All entries displayed with color-coded wins/losses.
✅ Key stats – Total trades, win rate, and RR sum in the top row.
✅ Quick insights – Spot trends, refine your strategy, and track performance without spreadsheets.
How to Use
1️⃣ Open settings and enter R-values, one per line (e.g., 2.5, -1, 3.2) along with short comments (bad entry, counter trend, etc)
2️⃣ View the table in the top-right corner of your chart.
3️⃣ Analyze your results, adjust your strategy, and improve consistency.
Perfect for manual backtesters who want a fast, no-spreadsheet solution. 🚀
Wyckoff Event Detection [Alpha Extract]Wyckoff Event Detection
A powerful and intelligent indicator designed to detect key Wyckoff events in real time, helping traders analyze market structure and anticipate potential trend shifts. Using volume and price action, this script automatically identifies distribution and accumulation phases, providing traders with valuable insights into market behavior.
🔶 Phase-Based Detection
Utilizes a phase detection algorithm that evaluates price and volume conditions to identify accumulation (bullish) and distribution (bearish) events. This method ensures the script effectively captures major market turning points and avoids noise.
🔶 Multi-Factor Event Recognition
Incorporates multiple event conditions, including upthrusts, selling climaxes, and springs, to detect high-probability entry and exit points. Each event is filtered through customizable sensitivity settings, ensuring precise detection aligned with different trading styles.
🔶 Customizable Parameters
Fine-tune event detection with adjustable thresholds for volume, price movement, trend strength, and event spacing. These inputs allow traders to personalize the script to match their strategy and risk tolerance.
// === USER INPUTS ===
i_volLen = input.int(20, "Volume MA Length", minval=1)
i_priceLookback = input.int(20, "Price Pattern Lookback", minval=5)
i_lineLength = input.int(15, "Line Length", minval=5)
i_labelSpacing = input.int(5, "Minimum Label Spacing (bars)", minval=1, maxval=20)
❓How It Works
🔶 Event Identification
The script scans for key Wyckoff events by analyzing volume spikes, price deviations, and trend shifts within a user-defined lookback period. It categorizes events into bullish (accumulation) or bearish (distribution) structures and plots them directly on the chart.
// === EVENT DETECTION ===
volMA = ta.sma(volume, i_volLen)
highestHigh = ta.highest(high, i_priceLookback)
lowestLow = ta.lowest(low, i_priceLookback)
🔶 Automatic Filtering & Cleanup
Unconfirmed or weak signals are filtered out using customizable strength multipliers and volume thresholds. Events that do not meet the minimum conditions are discarded to keep the chart clean and informative.
🔶 Phase Strength Analysis
The script continuously tracks bullish and bearish event counts to determine whether the market is currently in an accumulation, distribution, or neutral phase. This allows traders to align their strategies accordingly.
🔶 Visual Alerts & Labels
Detects and labels key Wyckoff events directly on the chart, providing immediate insights into market conditions:
- PSY (Preliminary Supply) and UT (Upthrust) for distribution phases.
- PS (Preliminary Support) and SC (Selling Climax) for accumulation phases.
- Labels adjust dynamically to avoid chart clutter and improve readability.
🔶 Entry & Exit Optimization
By highlighting supply and demand imbalances, the script assists traders in identifying optimal entry and exit points. Wyckoff concepts such as springs and upthrusts provide clear trade signals based on market structure.
🔶 Trend Confirmation & Risk Management
Observing how price reacts to detected events helps confirm trend direction and potential reversals. Traders can place stop-loss and take-profit levels based on Wyckoff phase analysis, ensuring strategic trade execution.
🔶 Table-Based Market Analysis (Table)
A built-in table summarizes:
- Market Phase: Accumulation, Distribution, or Neutral.
- Strength of Phase: Weak, Moderate, or Strong.
- Price Positioning: Whether price is near support, resistance, or in a trading range.
- Supply/Demand State: Identifies whether the market is supply or demand dominant.
🔶 Why Choose Wyckoff Market Phases - Alpha Extract?
This indicator offers a systematic approach to understanding market mechanics through the lens of Wyckoff's time-tested principles. By providing clear and actionable insights into market phases, it empowers traders to make informed decisions, enhancing both confidence and performance in various trading environments.
CAM| Bar volatility and statsCAPRICORN ASSETS MANAGEMENT
⸻
CAM | Bar Volatility and Stats Indicator
The CAM | Bar Volatility and Stats indicator is designed to track historical price movements, analyzing bar volatility and key statistical trends in financial instruments. By evaluating past bars, it provides insights into market dynamics, helping traders assess volatility, trend strength, and momentum patterns.
Key Features & Functionality:
✅ Volatility Analysis – Measures historical volatility by calculating the average price range per bar and displaying it in pips.
✅ Bull & Bear Bar Statistics – Tracks the number of bullish and bearish bars within a given lookback period, including their respective percentages.
✅ Consecutive Bar Sequences – Identifies and records the longest streaks of consecutive bullish or bearish bars, providing insights into market trends.
✅ Average Volatility by Trend – Computes separate volatility values for bullish and bearish bars, helping traders understand trend-based price behavior.
✅ Real-Time Labeling – Displays a live statistics summary directly on the chart, updating dynamically with each new bar.
Benefits for Traders:
📊 Enhanced Market Insight – Quickly assess market conditions, determining whether volatility is increasing or decreasing.
📈 Trend Strength Identification – Identify strong bullish or bearish sequences to improve trade timing and strategy development.
⏳ Better Risk Management – Use historical volatility metrics to fine-tune stop-loss and take-profit levels.
🛠 Customizable Analysis – Adjustable lookback period and display options allow traders to focus on the data that matters most.
This indicator is an essential tool for traders looking to refine their decision-making process by leveraging volatility-based statistics. Whether trading Forex, stocks, or commodities, it provides valuable insights into price action trends and market conditions.
⸻
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights.
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
