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Micro Futures Contract Calculator Micro Futures Contract Calculator Synopsis: The Micro Futures Contract Calculator is a sleek, minimalist indicator that calculates the number of Micro E-mini Nasdaq-100 (MNQ) or S&P 500 (MES) contracts you can trade based on a fixed dollar risk and stop-loss (in ticks). Displayed in a compact, professional table in the top-right corner, it shows your risk, stop-loss, contract type, and calculated contracts, helping traders maintain consistent risk management. How to Use: Add the indicator to your chart (search “Micro Futures Contract Calculator”). In settings, input: Maximum Risk ($): Your total risk per trade (e.g., $100). Stop-Loss (Ticks): Stop-loss size in ticks (e.g., 20 ticks = 5 points). Contract Type: Select MNQ or MES. Check the top-right table for: Risk, stop-loss, contract type, and number of contracts (e.g., “10” for MNQ, “4” for MES). Use the contract number to size trades, ensuring risk stays fixed. Why Standardized Risk is Important: Consistency: Fixed risk per trade (e.g., $100) prevents oversized losses, stabilizing long-term performance. Discipline: Removes emotional guesswork, enforcing a systematic approach across MNQ/MES trades. Capital Protection: Limits exposure, preserving your account during losing streaks and volatile markets. Scalability: Aligns position sizing with your risk tolerance, enabling confident scaling as your account grows. This indicator simplifies risk management, making it essential for disciplined futures trading.
Pine Script® göstergesi
xxBoomerxx tarafından
Signalgo XThis script delivers a multi-layered approach to real-time news, hype, and institutional activity detection across different timeframes. Unlike traditional indicators or simple news overlays, this tool uses multiple and different analytics with a proprietary anti-hype filter and institutional tracking system. The indicator does not use external news headlines or economic calendar events. Instead, it generates "news" signals in real time by analyzing price, volume, volatility, and sentiment data across multiple timeframes. These signals are algorithmically classified as "bullish news," "bearish news," "strong, or "hype" events, and are displayed as chart labels. The script also includes a proprietary anti-hype filter that suppresses signals during periods of abnormal or unreliable market conditions.
Pine Script® göstergesi
signalgo tarafından
Global Risk Matrix [QuantAlgo]🟢 Overview The Global Risk Matrix is a comprehensive macro risk assessment tool that aggregates multiple global financial indicators into a unified risk sentiment framework. It transforms diverse economic data streams (from currency strength and liquidity measures to volatility indices and commodity prices) into standardized Z-Score readings to identify market regime shifts across risk-on and risk-off conditions. The indicator displays both a risk oscillator showing weighted average sentiment and a dynamic 2D matrix visualization that plots signal strength against momentum to reveal current market phase and historical evolution. This helps traders and investors understand broad market conditions, identify regime transitions, and align their strategies with prevailing macro risk environments across all asset classes. 🟢 How It Works The indicator employs Z-Score normalization across various global macro components, each representing distinct aspects of market liquidity, sentiment, and economic health. Raw data from sources like DXY, S&P 500, Fed liquidity, global M2 money supply, VIX, and commodities undergoes statistical standardization. Several components are inverted (USDT.D, DXY, VIX, credit spreads, treasury bonds, gold) to align with risk-on interpretation, where positive values indicate bullish conditions. This unique system applies configurable weights to each component based on selected asset class presets (Crypto Investor/Trader, Stock Trader, Commodity Trader, Forex Trader, Risk Parity, or Custom), creating a weighted average Z-Score. It then analyzes both signal strength and momentum direction to classify market conditions into four distinct phases: Risk-On (positive signal, rising momentum), Risk-Off (negative signal, falling momentum), Recovery (negative signal, rising momentum), and Weakening (positive signal, falling momentum). The 2D matrix visualization plots these dimensions with historical trail tracking to show regime evolution over time. 🟢 How to Use 1. Risk Oscillator Interpretation and Phase Analysis Positive Territory (Above Zero) : Indicates risk-on conditions with capital flowing toward growth assets and higher risk tolerance Negative Territory (Below Zero) : Signals risk-off sentiment with capital seeking safety and defensive positioning Extreme Levels (±2.0) : Represent statistically significant deviations that often precede regime reversals or trend exhaustion Zero Line Crosses : Mark critical transitions between risk regimes, providing early signals for portfolio rebalancing Phase Color Coding : Green (Risk-On), Red (Risk-Off), Blue (Recovery), Yellow (Weakening) for immediate regime identification 2. Risk Matrix Visualization and Trail Analysis Current Position Marker (⌾) : Shows real-time location in the risk/momentum space for immediate situational awareness Historical Trail : Connected path showing recent market evolution and regime transition patterns Quadrant Analysis : Risk-On (upper right), Risk-Off (lower left), Recovery (lower right), Weakening (upper left) Trail Patterns : Clockwise rotation typically indicates healthy regime cycles, while erratic movement suggests uncertainty 3. Pro Tips for Trading and Investing → Portfolio Allocation Filter : Use Risk-On phases to increase exposure to growth assets, small caps, and emerging markets while reducing defensive positions during confirmed green phases → Entry Timing Enhancement : Combine Recovery phase signals with your technical analysis for optimal long entry points when macro headwinds are clearing but prices haven't fully recovered → Risk Management Overlay : Treat Weakening phase transitions as early warning systems to tighten stop losses, reduce position sizes, or hedge existing positions before full Risk-Off conditions develop → Sector Rotation Strategy : During Risk-On periods, favor cyclical sectors (technology, consumer discretionary, financials) while Risk-Off phases favor defensive sectors (utilities, consumer staples, healthcare) → Multi-Timeframe Confluence : Use daily matrix readings for strategic positioning while applying your regular technical analysis on lower timeframes for precise entry and exit execution → Divergence Detection : Watch for situations where your asset shows bullish technical patterns while the matrix shows Risk-Off conditions—these often provide the highest probability short opportunities and vice versa
Pine Script® göstergesi
QuantAlgo tarafından
Position Averaging CalculatorDescription: A powerful utility indicator for active traders. Input up to 10 averaging trades (entry price and dollar amount), and get a real-time calculation of: Average position price Spread (%) between last entry and average Total position size Potential profit based on a custom sell price All inputs are editable directly in the indicator settings. A clean table display shows detailed breakdowns for fast decision-making during trade management.
Pine Script® göstergesi
CryptoIngener tarafından
EMA CCI SSL BUY SELL Signal [CongTrader]📌 Indicator Description EMA CCI SSL BUY SELL Signal is a powerful trading tool that combines HTF SSL Channel, EMA trend filtering, and precise crossover-based signals to generate high-probability BUY and SELL entries. It is designed to work effectively in crypto, forex, and stock markets, especially on 15m, 1H, and 4H timeframes. 🔍 Key Features: ✅ Clear BUY / SELL labels with visual markers. 📈 EMA trend filter helps eliminate false signals in sideways or weak trend markets. ⏫ SSL Channel is calculated from higher timeframe data for increased accuracy. 🔔 Built-in alerts to notify you when a new signal is triggered. 🧠 Informative price & percentage change table shown directly on the chart. 📊 Regression channel included to help analyze trend direction visually. 🧾 How to Use Add the indicator to your chart and choose your preferred timeframe (recommended: 15min, 1H, or 4H). Customize the EMA length and switch between Auto / Manual HTF Mode to suit your strategy. Watch for: BUY signals with green “BUY” labels and upward arrows. SELL signals with red “SELL” labels and downward arrows. Signal table showing entry price and % change since signal. Enable alerts to be notified of new BUY/SELL signals. For best results, combine this tool with your own price action analysis and risk management strategy. 🙏 Thank You Thank you for using the CongTrader indicator! We strive to provide useful and easy-to-understand trading tools to help traders across different markets. If you find this indicator helpful, please consider leaving a like ❤️, sharing your feedback, or recommending it to others in the community! ⚠️ Disclaimer This is a technical analysis tool intended for educational and informational purposes only. It does not constitute financial or investment advice. Past performance is not indicative of future results. Always trade responsibly and use proper risk management. EMA Buy Sell Signal, SSL Channel Indicator, HTF Trend Filter, Crypto Signal Tool, Forex Buy Sell Alert, CongTrader Indicator, TradingView Signal Script, EMA Crossover Strategy, Regression Channel, Best TradingView Indicator.
Pine Script® göstergesi
CongTrader_ tarafından
Visual SL/TP con ATR + Pips/TicksThis indicator automatically displays the current ATR size along with suggested SL (Stop Loss) and TP (Take Profit) values, expressed in key units such as pips and ticks. ✅ Compatible with: Forex (e.g., EURUSD) Indices (e.g., NAS100, US30) Gold (XAUUSD) Cryptocurrencies (e.g., XRPUSDT) 🎯 Ideal for scalping, intraday, or swing trading. 🧠 Saves calculation time and improves trading speed. Includes: Automatic SL/TP calculation based on ATR multiples Conversion to pips and ticks for quick reading Dynamic support for different instrument types 📌 Tip: Use this indicator alongside your entry strategy with EMAs or volume for more precise trading.
Pine Script® göstergesi
angelofarinha97 tarafından
2
Assets Correlation by GDM📊 Correlation Matrix Table between Two Assets This indicator calculates and displays the rolling correlation between the asset on your chart and a second asset of your choice. The correlation is computed based on log returns over a user-defined lookback period. A live summary table appears in the bottom left corner, providing a real-time snapshot of the current correlation and its context. How it works: Comparison Asset: Select any symbol to compare with the chart asset (e.g., compare BTCUSD to ETHUSD). Lookback Period: Choose the rolling window (in bars) used to calculate the Pearson correlation coefficient. Dynamic Table: A table in the lower left corner summarizes: Main asset symbol Comparison symbol Analysis period (bars) Current correlation value (rounded to 2 decimals) Correlation strength & direction (Strong, Moderate, Weak | Positive/Negative) Visual Plot: The indicator plots the correlation value over time so you can observe changes and trends. Table Positioning: Table location can be adjusted from settings (bottom left/right, top left/right). How to use: Risk Management & Diversification: Quickly assess if two assets move together (positive correlation), in opposite directions (negative correlation), or independently. Pairs Trading: Identify opportunities when correlation diverges from historical norms. Portfolio Construction: Avoid overexposure to highly correlated assets, or use negative correlation for hedging. Limitations & Tips: Correlation values are based on historical returns and may change during periods of market stress or volatility. Use multiple lookback periods (short, medium, long) for a more robust view. Correlation does not imply causation—always complement with additional analysis. Script Features: User-selectable comparison asset and lookback window. Real-time correlation calculation. Clean summary table with correlation stats. Optional alert logic and correlation plot for more advanced usage. If you find this indicator useful, please leave a like and let me know your suggestions for improvements!
Pine Script® göstergesi
GiuseppeDeMartino tarafından
Risk and Position Sizing📏 Why Position Size Should Be Based on Risk? Let’s say you are ready to lose 1,000 in a trade. Based on your stop loss level, you can calculate how many shares (or quantity) to buy, so that if the stop hits, you only lose that ₹1,000. This is called risk-based position sizing. It makes your trade size dynamic — small when SL is wide, bigger when SL is tight. No more random position sizes — just systematic. Portfolio size is multiplied by the selected risk % to get money risk per trade. This amount is then used to calculate how many shares can be bought for the given stop-loss. So chose your portfolio size in settings. Default Portfolio size is 1,00,000 . You can select your risk % per portfolio in the settings — for example: 0.25% for conservative style 0.5% to 1% for balanced traders 1.25% or 1.5% for aggressive ones (not recommended for beginners) This script will automatically calculate how much quantity you should buy, for each stop-loss scenario. 📈 Progressive & Inverse-Progressive Risk Styles Some traders follow progressive position sizing — they start with small risk when the trend is just starting, and increase the risk % as the trend confirms. Others follow inverse-progressive sizing — they take high risk at early stages of a bull market, and reduce risk as the trend matures (when upside becomes limited). 📌 This script allows you to manually control the risk % in settings, so you can adjust it based on your trading phase and style. 📋 Three SL Scenarios – Choose What Matches Your Style The table shows three different stop-loss conditions, and for each one it calculates: Today’s Low – tightest stop loss Yesterday’s Low – slightly safer, ideal for short-term swing trades EMA Stop (configurable) – gives more breathing room. You can visually compare all 3 in the table and choose whichever fits your strategy and comfort. Also, you can customize: Theme: dark or light Font size Table position (upper/lower corners) 🧠 Designed for traders who take risk management seriously. Let this script handle the math. You focus on execution. Happy Trading! – LensOfChartist
Pine Script® göstergesi
LensOfChartist tarafından
SIP Evaluator and Screener [Trendoscope®]The SIP Evaluator and Screener is a Pine Script indicator designed for TradingView to calculate and visualize Systematic Investment Plan (SIP) returns across multiple investment instruments. It is tailored for use in TradingView's screener, enabling users to evaluate SIP performance for various assets efficiently. 🎲 How SIP Works A Systematic Investment Plan (SIP) is an investment strategy where a fixed amount is invested at regular intervals (e.g., monthly or weekly) into a financial instrument, such as stocks, mutual funds, or ETFs. The goal is to build wealth over time by leveraging the power of compounding and mitigating the impact of market volatility through disciplined, consistent investing. Here’s a breakdown of how SIPs function: Regular Investments : In an SIP, an investor commits to investing a fixed sum at predefined intervals, regardless of market conditions. This consistency helps inculcate a habit of saving and investing. Cost Averaging : By investing a fixed amount regularly, investors purchase more units when prices are low and fewer units when prices are high. This approach, known as dollar-cost averaging, reduces the average cost per unit over time and mitigates the risk of investing a large amount at a peak price. Compounding Benefits : Returns generated from the invested amount (e.g., capital gains or dividends) are reinvested, leading to exponential growth over the long term. The longer the investment horizon, the greater the potential for compounding to amplify returns. Dividend Reinvestment : In some SIPs, dividends received from the underlying asset can be reinvested to purchase additional units, further enhancing returns. Taxes on dividends, if applicable, may reduce the reinvested amount. Flexibility and Accessibility : SIPs allow investors to start with small amounts, making them accessible to a wide range of individuals. They also offer flexibility in terms of investment frequency and the ability to adjust or pause contributions. In the context of the SIP Evaluator and Screener , the script simulates an SIP by calculating the number of units purchased with each fixed investment, factoring in commissions, dividends, taxes and the chosen price reference (e.g., open, close, or average prices). It tracks the cumulative investment, equity value, and dividends over time, providing a clear picture of how an SIP would perform for a given instrument. This helps users understand the impact of regular investing and make informed decisions when comparing different assets in TradingView’s screener. It offers insights into key metrics such as total invested amount, dividends received, equity value, and the number of installments, making it a valuable resource for investors and traders interested in understanding long-term investment outcomes. 🎲 Key Features Customizable Investment Parameters: Users can define the recurring investment amount, price reference (e.g., open, close, HL2, HLC3, OHLC4), and whether fractional quantities are allowed. Commission Handling: Supports both fixed and percentage-based commission types, adjusting calculations accordingly. Dividend Reinvestment: Optionally reinvests dividends after a user-specified period, with the ability to apply tax on dividends. Time-Bound Analysis: Allows users to set a start year for the analysis, enabling historical performance evaluation. Flexible Dividend Periods: Dividends can be evaluated based on bars, days, weeks, or months. Visual Outputs: Plots key metrics like total invested amount, dividends, equity value, and remainder, with customizable display options for clarity in the data window and chart. 🎲 Using the script as an indicator on Tradingview Supercharts In order to use the indicator on charts, do the following. Load the instrument of your choice - Preferably a stable stocks, ETFs. Chose monthly timeframe as lower timeframes are insignificant in this type of investment strategy Load the indicator SIP Evaluator and Screener and set the input parameters as per your preference. Indicator plots, investment value, dividends and equity on the chart. 🎲 Visualizations Installments : Displays the number of SIP installments (gray line, visible in the data window). Invested Amount : Shows the cumulative amount invested, excluding reinvested dividends (blue area plot). Dividends : Tracks total dividends received (green area plot). Equity : Represents the current market value of the investment based on the closing price (purple area plot). Remainder : Indicates any uninvested cash after each installment (gray line, visible in the data window). 🎲 Deep dive into the settings The SIP Evaluator and Screener offers a range of customizable settings to tailor the Systematic Investment Plan (SIP) simulation to your preferences. Below is an explanation of each setting, its purpose, and how it impacts the analysis: 🎯 Duration Start Year (Default: 2020) : Specifies the year from which the SIP calculations begin. When Start Year is enabled via the timebound option, the script only considers data from the specified year onward. This is useful for analyzing historical SIP performance over a defined period. If disabled, the script uses all available data. Timebound (Default: False) : A toggle to enable or disable the Start Year restriction. When set to False, the SIP calculation starts from the earliest available data for the instrument. 🎯 Investment Recurring Investment (Default: 1000.0) : The fixed amount invested in each SIP installment (e.g., $1000 per period). This represents the regular contribution to the SIP and directly influences the total invested amount and quantity purchased. Allow Fractional Qty (Default: True) : When enabled, the script allows the purchase of fractional units (e.g., 2.35 shares). If disabled, only whole units are purchased (e.g., 2 shares), with any remaining funds carried forward as Remainder. This setting impacts the precision of investment allocation. Price Reference (Default: OPEN): Determines the price used for purchasing units in each SIP installment. Options include: OPEN : Uses the opening price of the bar. CLOSE : Uses the closing price of the bar. HL2 : Uses the average of the high and low prices. HLC3 : Uses the average of the high, low, and close prices. OHLC4 : Uses the average of the open, high, low, and close prices. This setting affects the cost basis of each purchase and, consequently, the total quantity and equity value. 🎯 Commission Commission (Default: 3) : The commission charged per SIP installment, expressed as either a fixed amount (e.g., $3) or a percentage (e.g., 3% of the investment). This reduces the amount available for purchasing units. Commission Type (Default: Fixed) : Specifies how the commission is calculated: Fixed ($) : A flat fee is deducted per installment (e.g., $3). Percentage (%) : A percentage of the investment amount is deducted as commission (e.g., 3% of $1000 = $30). This setting affects the net amount invested and the overall cost of the SIP. 🎯 Dividends Apply Tax On Dividends (Default: False) : When enabled, a tax is applied to dividends before they are reinvested or recorded. The tax rate is set via the Dividend Tax setting. Dividend Tax (Default: 47) : The percentage of tax deducted from dividends if Apply Tax On Dividends is enabled (e.g., 47% tax reduces a $100 dividend to $53). This reduces the amount available for reinvestment or accumulation. Reinvest Dividends After (Default: True, 2) : When enabled, dividends received are reinvested to purchase additional units after a specified period (e.g., 2 units of time, defined by Dividends Availability). If disabled, dividends are tracked but not reinvested. Reinvestment increases the total quantity and equity over time. Dividends Availability (Default: Bars) : Defines the time unit for evaluating when dividends are available for reinvestment. Options include: Bars : Based on the number of chart bars. Weeks : Based on weeks. Months : Based on months (approximated as 30.5 days). This setting determines the timing of dividend reinvestment relative to the Reinvest Dividends After period. 🎯 How Settings Interact These settings work together to simulate a realistic SIP. For example, a $1000 recurring investment with a 3% commission and fractional quantities enabled will calculate the number of units purchased at the chosen price reference after deducting the commission. If dividends are reinvested after 2 months with a 47% tax, the script fetches dividend data, applies the tax, and adds the net dividend to the investment amount for that period. The Start Year and Timebound settings ensure the analysis aligns with the desired timeframe, while the Dividends Availability setting fine-tunes dividend reinvestment timing. By adjusting these settings, users can model different SIP scenarios, compare performance across instruments in TradingView’s screener, and gain insights into how commissions, dividends, and price references impact long-term returns. 🎲 Using the script with Pine Screener The main purpose of developing this script is to use it with Tradingview Pine Screener so that multiple ETFs/Funds can be compared. In order to use this as a screener, the following things needs to be done. Add SIP Evaluator and Screener to your favourites (Required for it to be added in pine screener) Create a watch list containing required instruments to compare Open pine screener from Tradingview main menu Products -> Screeners -> Pine or simply load the URL - www.tradingview.com Select the watchlist created from Watchlist dropdown. Chose the SIP Evaluator and Screener from the "Choose Indicator" dropdown Set timeframe to 1 month and update settings as required. Press scan to display collected data on the screener. 🎲 Use Case This indicator is ideal for educational purposes, allowing users to experiment with SIP strategies across different instruments. It can be applied in TradingView’s screener to compare SIP performance for stocks, ETFs, or other assets, helping users understand how factors like commissions, dividends, and price references impact returns over time.
Pine Script® göstergesi
Trendoscope tarafından
2
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions. How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?" Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5). Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values. ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility. Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant. Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points. Key Benefits: Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility. Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement. Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations. Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes. Setup Parameters (Inputs) When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters: 1. Symbol Preset: Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument. Options: MNQ (Micro Nasdaq 100 Futures) MES (Micro E-mini S&P 500 Futures) MGC (Micro Gold Futures) MCL (Micro Crude Oil Futures) Stock (Generic stock setting, with tick size/value of 0.01) Custom (Allows you to manually input tick size and value) Default: MNQ Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading. 2. Tick Size (Manual Override): Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument. Type: Float Default: 0.25 Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode. 3. Tick Value (Manual Override): Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment. Type: Float Default: 0.50 Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible. 4. Default Risk ($): Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value. Type: Float Default: 50.0 Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk. ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss. 5. ATR Offset Length: Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset. Type: Integer Default: 7 Hidden: This input is hidden (display=display.none). 6. ATR Offset Timeframe: Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe. Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily) Default: "1" (1 Minute) Hidden: This input is hidden (display=display.none). 7. ATR Offset Multiplier (x ATR): Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added. Type: Float Minimum Value: 0 (no offset) Default: 1.0 Hidden: This input is hidden (display=display.none).
Pine Script® göstergesi
rduatg tarafından
Multi-Session MarkerMulti-Session Marker is a flexible visual tool for traders who want to highlight up to 10 custom trading sessions directly on their chart’s background. Custom Sessions: Enter up to 10 time ranges (in HHMM-HHMM format) to mark any market session, news window, or personal focus period. Visual Clarity: For each session, toggle the highlight on or off and select a unique background color and opacity, making it easy to distinguish active trading windows at a glance. Universal Time Handling: Session times automatically follow your chart’s time zone—no manual adjustment required. Efficient and Fast: Utilizes TradingView’s bgcolor() for smooth performance, even on fast timeframes like 1-second charts. Clean Interface: All session controls are grouped for easy editing in the indicator’s settings panel. How to use: In the indicator settings, enter your desired session times (e.g., 0930-1130) for each session you want to highlight. Toggle “Show Session” and pick a color for each session. The background will automatically highlight those periods on your chart. This indicator is ideal for day traders, futures traders, or anyone who wants to visually segment their trading day for better focus and analysis.
Pine Script® göstergesi
TBoneTrina tarafından
Hidden Markov Model [Extension] | FractalystWhat's the indicator's purpose and functionality? The Hidden Markov Model is specifically designed to integrate with the Quantify Trading Model framework, serving as a probabilistic market regime identification system for institutional trading analysis. Hidden Markov Models are particularly well-suited for market regime detection because they can model the unobservable (hidden) state of the market, capture probabilistic transitions between different states, and account for observable market data that each state generates. The indicator uses Hidden Markov Model mathematics to automatically detect distinct market regimes such as low-volatility bull markets, high-volatility bear markets, or range-bound consolidation periods. This approach provides real-time regime probabilities without requiring optimization periods that can lead to overfitting, enabling systematic trading based on genuine probabilistic market structure. How does this extension work with the Quantify Trading Model? The Hidden Markov Model | Fractalyst serves as a probabilistic state estimation engine for systematic market analysis. Instead of relying on traditional technical indicators, this system automatically identifies market regimes using forward algorithm implementation with three-state probability calculation (bullish/neutral/bearish), Viterbi decoding process for determining most likely regime sequence without repainting, online parameter learning with adaptive emission probabilities based on market observations, and multi-feature analysis combining normalized returns, volatility comprehensive regime assessment. The indicator outputs regime probabilities and confidence levels that can be used for systematic trading decisions, portfolio allocation, or risk management protocols. Why doesn't this use optimization periods like other indicators? The Hidden Markov Model | Fractalyst deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses a fixed mathematical framework based on Hidden Markov Model theory rather than optimized parameters, probabilistic state estimation using forward algorithm calculations that work across all market conditions, online learning methodology with adaptive parameter updates based on real-time market observations, and regime persistence modeling using fixed transition probabilities with 70% diagonal bias for realistic regime behavior. This approach ensures the regime detection signals remain robust across different market cycles without the performance degradation typical of over-optimized traditional indicators. Can this extension be used independently for discretionary trading? No, the Hidden Markov Model | Fractalyst is specifically engineered for systematic implementation within institutional trading frameworks. The indicator is designed to provide regime filtering for systematic trading algorithms and risk management systems, enable automated backtesting through mathematical regime identification without subjective interpretation, and support institutional-level analysis when combined with systematic entry/exit models. Using this indicator independently would miss the primary value proposition of systematic regime-based strategy optimization that institutional frameworks provide. How do I integrate this with the Quantify Trading Model? Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation: - Add both HMM Extension and Quantify Trading Model to your chart - Select HMM Extension as the bias source using input.source() - Quantify automatically uses the extension's bias signals for entry/exit analysis - The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, and market structure patterns identified by the extension The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation What markets and assets does the indicator Extension work best on? The Hidden Markov Model | Fractalyst performs optimally on markets with sufficient price movement since the system relies on statistical analysis of returns, volatility, and momentum patterns for regime identification. Recommended asset classes include major forex pairs (EURUSD, GBPUSD, USDJPY) with high liquidity and clear regime transitions, stock index futures (ES, NQ, YM) providing consistent regime behavior patterns, individual equities (large-cap stocks with sufficient volatility for regime detection), cryptocurrency markets (BTC, ETH with pronounced regime characteristics), and commodity futures (GC, CL showing distinct market cycles and regime transitions). These markets provide sufficient statistical variation in returns and volatility patterns, ensuring the HMM system's mathematical framework can effectively distinguish between bullish, neutral, and bearish regime states. Any timeframe from 15-minute to daily charts provides sufficient data points for regime calculation, with higher timeframes (4H, Daily) typically showing more stable regime identification with fewer false transitions, while lower timeframes (30m, 1H) provide more responsive regime detection but may show increased noise. Acceptable Timeframes and Portfolio Integration: - Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation. Legal Disclaimers and Risk Acknowledgments Trading Risk Disclosure The HMM Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns. Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate analysis. The extension's performance depends on accurate data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy. System Dependency Acknowledgment The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior. Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance. Intellectual Property Protection The HMM Extension, including all proprietary algorithms, classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action. Liability Limitation By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension. Past performance of bias detection accuracy, classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst. User Responsibility Statement Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection. This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate analysis assumptions. Terms of Service Acceptance Continued use of the HMM Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
Pine Script® göstergesi
Fractalyst tarafından
TradePlanner ProPlan smarter. Trade with precision. TradePlanner Pro is a professional-grade overlay tool designed to streamline your trading decisions by visually organizing your trade plans directly on the chart. Built for traders who value preparation and clarity, this script enables precise entry planning, risk management, and target visualization—all tailored per symbol. Core Purpose TradePlanner Pro helps you map out potential trades using pre-defined symbol-based presets. It dynamically calculates position sizes based on your account size or fixed risk, then visualizes key trade levels (Entry, Take Profits, Stop Loss) with profit/loss metrics in both dollar and percentage terms. It's the perfect companion for traders who prepare their setups in advance and want their plans clearly represented on the chart. Key Features 🔹 Per-Symbol Presets: Define entries, up to 3 take-profit levels, and stop-losses for each ticker. 🔹 Dynamic Risk Sizing: Choose between percentage-based risk or fixed dollar risk per trade. 🔹 Visual Trade Mapping: Automatically plots Entry, TP1–TP3, and SL lines on your chart. 🔹 Real-Time P&L Labels: Displays profit/loss amounts and percentages, with optional R/R ratios. 🔹 Custom Investment Display: Shows how much capital is allocated per trade. 🔹 Clean, Configurable UI: Adjust label positions, font sizes, opacity, and label visibility to match your style. Whether you're swing trading or day trading, TradePlanner Pro helps you stay disciplined, organized, and confident in your execution. How to Use TradePlanner Pro – Step-by-Step Guide TradePlanner Pro is designed to be easy to set up while giving you full control over how your trades are visualized and calculated. Here’s how to get started: 1. Start with Default Settings By default, the script assumes: Account Size: $10,000 Max Money per Trade (%): 1.0% Max Risk (USD): 0 (disabled; only percentage risk is used) This means the script will size each trade to risk 1% of your account balance per trade unless you override it with a fixed USD risk amount. 2. Set Up Your Symbol Presets The "Symbol Presets" input is a flexible text area where you define trade setups for each ticker. Format (one per line): SYMBOL:Entry,TP1 ,SL Example: AAPL:250,260,270,240 MSFT:100,110,90 TSLA:180,200,170 You can include 1 to 3 take-profit levels. The script will only activate for the current chart’s symbol, matching what's listed. 3. Customize Risk Parameters You can use: Account % Risk – Based on account size and % risk. Fixed USD Risk – When a dollar amount is entered (>0), it takes priority and calculates share size based on the risk per share. There's also an option to round share quantities down to whole units, which is useful for stock or crypto trading platforms that only allow whole-number units. 4. Choose What to Display Toggle on/off these elements as needed: Show Entry/TP/SL Lines Show P&L Labels – Profit/loss amounts at each target and SL. Show Amount Invested – Includes total dollar value in the quantity label. Show Percentages – Adds % gain/loss to each label. Show Risk/Reward Ratios – Optionally displayed beside or below TP labels. You can further adjust: Font size and label opacity Label position offset – In percent of price range, so they don’t overlap the actual levels. 5. Read the Visual Outputs Once the preset matches the current chart symbol: Lines will appear for Entry, TP1-TP3, and Stop Loss. Labels will display your: Trade quantity (and invested amount) Dollar and % profit at each target Total loss at stop loss Optional R/R ratios Everything updates dynamically and adjusts to your current chart scale and bar availabilit
Pine Script® göstergesi
yairmish tarafından
VWAP/VOL [Extension] | FractalystWhat's the indicator's purpose and functionality? The VWAP/VOL Extension is designed specifically as a bias identification system for the Quantify Trading Model. This extension uses volume-weighted average price analysis combined with institutional volume classification to automatically detect market bias without requiring optimization periods that lead to overfitting. The system provides real-time bias signals (bullish/bearish/neutral) that integrate directly with Quantify's machine learning algorithms, enabling institutional-level backtesting and automated entry/exit identification based on genuine market structure rather than curve-fitted parameters. How does this extension work with the Quantify Trading Model? The VWAP/VOL Extension serves as the bias detection engine for Quantify's automated trading system. Instead of manually selecting bias direction, this extension automatically identifies market bias using: - Volume-weighted VWAP analysis with three-state detection (bullish/bearish/neutral) - Institutional volume classification using relative volume thresholds without optimization - Non-repainting architecture ensuring consistent bias signals for Quantify's machine learning The extension outputs bias signals that Quantify uses as input through the `input.source()` function, allowing the Trading Model to focus on optimal entry/exit timing while the extension handles bias identification. Why doesn't this use optimization periods like other indicators? The VWAP/VOL Extension deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses: - Fixed mathematical thresholds based on market structure principles rather than optimized parameters - Relative volume analysis using standard 2.0x/0.5x ratios that work across all market conditions - VWAP distance calculations based on percentage thresholds without curve-fitting - Gap enforcement using fixed 5-bar minimums for disciplined bias detection This approach ensures the bias signals remain robust across different market regimes without the performance degradation typical of over-optimized systems. Can this extension be used independently for discretionary trading? No, the VWAP/VOL Extension is specifically engineered to work as a component within the Quantify ecosystem. The extension is designed to: - Provide bias input for Quantify's machine learning algorithms - Enable automated backtesting through systematic bias identification - Support institutional-level analysis when combined with Quantify's ML entry model Using this extension independently would miss the primary value proposition of systematic entry/exit optimization that Quantify provides. The extension handles bias detection so Quantify can focus on probability-based trade timing and risk management. How does this enable institutional-level backtesting? The extension transforms discretionary bias identification into systematic institutional analysis by: - Eliminating subjective bias selection through automated VWAP/volume analysis - Providing consistent historical signals with non-repainting architecture for accurate backtesting - Integrating with Quantify's algorithms to identify optimal entry patterns based on objective bias states - Enabling performance analysis across multiple market regimes without optimization bias This combination allows Quantify to run institutional-grade backtests with consistent bias identification, generating reliable performance statistics and risk metrics that reflect genuine market edge rather than curve-fitted results. How do I integrate this with the Quantify Trading Model? Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation: - Add both VWAP/VOL Extension and Quantify Trading Model to your chart - Select VWAP/VOL Extension as the bias source using input.source() - Quantify automatically uses the extension's bias signals for entry/exit analysis - The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, volume conviction, and market structure patterns identified by the extension The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation What markets and assets does the VWAP/VOL Extension work best on? The VWAP/VOL Extension performs optimally on markets with consistent, high-volume participation since the system relies on institutional volume analysis for bias detection. Futures markets provide the most reliable performance due to their centralized volume data and continuous institutional participation. Recommended Futures Markets: - ES (S&P 500 E-mini) - Over 2 million contracts daily volume, excellent liquidity depth - NQ (NASDAQ-100 E-mini) - Around 600,000 contracts daily, strong tech sector representation - YM (Dow Jones E-mini) - Consistent institutional flow and volume patterns - RTY (Russell 2000 E-mini) - Small-cap exposure with reliable volume data - GC (Gold Futures) - High volume commodity with institutional participation - CL (Crude Oil Futures) - Energy sector representation with strong volume consistency Why Futures Markets Excel: - Futures markets provide centralized volume reporting, ensuring the extension's volume classification system receives accurate institutional participation data. The standardized contract specifications and continuous trading hours create consistent volume patterns that the extension's algorithms can analyze effectively. Acceptable Timeframes and Portfolio Integration: - Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation. The extension is specifically designed to integrate with Quantify's portfolio management system, allowing multiple strategies across different timeframes and assets to operate simultaneously while maintaining consistent bias identification methodology across the entire automated trading portfolio. Legal Disclaimers and Risk Acknowledgments Trading Risk Disclosure The VWAP/VOL Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides volume-weighted institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns. Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate volume-based analysis. The extension's performance depends on accurate volume data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy. System Dependency Acknowledgment The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate volume reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior. Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange volume reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, volume reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance. Intellectual Property Protection The VWAP/VOL Extension, including all proprietary algorithms, volume classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action. Liability Limitation By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension. Past performance of bias detection accuracy, volume classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, volume pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst. User Responsibility Statement Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection. This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate volume-based analysis assumptions. Terms of Service Acceptance Continued use of the VWAP/VOL Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
Pine Script® göstergesi
Fractalyst tarafından
Bear Market Defender [QuantraSystems]Bear Market Defender A system to short Altcoins when BTC is ranging or falling - benefit from Altcoin bleed or collapse . QuantraSystems guarantees that the information created and published within this document and on the TradingView platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors. Important Note! The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script. Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance. This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest. Even More Important Note!! The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing. While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes. INTRODUCTION TO THE STAR FRAMEWORK The STAR Framework – an abbreviation for Strategic Trading with Adaptive Risk - is a bespoke portfolio-level infrastructure for dynamic, multi-asset crypto trading systems. It combines systematic position management, adaptive sizing, and “intra-system” diversification, all built on a rigorous foundation of Risk-based position sizing . At its core, STAR is designed to facilitate: Adaptive position sizing based on user-defined maximum portfolio risk Capital allocation across multiple assets with dynamic weight adjustment Execution-aware trading with robust fee and slippage adjustment Realistic equity curve logic based on a compounding realized PnL and additive unrealized PnL The STAR Framework is intended for use as both a standalone portfolio system or preferred as a modular component within a broader trading “global portfolio” - delivering a balance of robustness and scalability across strategy types, timeframes, and market regimes. RISK ALLOCATION VIA "R" CALCULATIONS The foundational concept behind STAR is the use of the R unit - a dynamic representation of risk per trade. R is defined by the distance between a trade's entry and its stoploss, making it an intuitive and universally adaptive sizing unit across any token, timeframe, or market. Example: Suppose the entry price is $100, and the stoploss is $95. A $5 move against the position represents a 1R loss. A 15% price increase to $115 would equal a +3R gain. This makes R-based systems highly flexible: the user defines the percentage of capital that is put at risk per R and all positions are scaled accordingly - whether the token is volatile, illiquid, or slow-moving. R is an advantageous method for determine position sizing - instead of being tied to complex value at risk mechanisms with having layered exit criteria, or continuous volatility-based sizing criteria that need to be adjusted while in an open trade, R allows for very straightforward sizing, invalidation and especially risk control – which is the most fundamental. REALIZED BALANCE, FEES & SLIPPAGE ACCOUNTING All position sizing, risk metrics, and the base equity curve within STAR are calculated based on realized balance only . This means: No sizing adjustments are made based on unrealized profit and loss ✅ No active positions are included in the system's realized equity until fully closed ✅ Every trade is sized precisely according to current locked-in realized portfolio balance ✅ This creates the safest risk profile - especially when multiple trades are open. Unrealized gains are not used to inflate sizing, ensuring margin safety across all assets. All calculations also incorporate slippage and fees, based on user-defined estimates – which can and should be based upon user-collected data - and updated frequently forwards in time. These are not cosmetic, or simply applied to the final equity curve - they are fully integrated into the dynamic position sizing and equity performance , ensuring: Stoploss hits result in exactly a −1R loss, even after slippage and fees ✅ Winners are discounted based on realistic execution costs ✅ No trade is oversized due to unaccounted execution costs ✅ Example - Slippage in R Units: Let R be defined as the distance from entry to stoploss. Suppose that distance is $1, and the trade is closed at a win of +$2. If execution slippage leads to a 50 cent worse entry and a 50 cent worse exit, you’ve lost $1 extra - which is an additional 1R in execution slippage. This makes the effective return 1.0R instead of the intended 2.0R. This is equivalent to a slippage value of 50%. Thus, slippage in STAR is tracked and modelled on an R-adjusted basis , enabling more accurate long-term performance modelling. MULTI-ASSET, LONG/SHORT SUPPORT STAR supports concurrent long and short positions across multiple tokens. This can sometimes result in partially hedged exposure - for example, being long one asset and short another. This structure has key benefits: Diversifies idiosyncratic risk by distributing exposure across multiple tokens Allows simultaneous exploitation of relative strength and weakness Reduces portfolio volatility via natural hedging during reduced trending periods Even in a highly correlated market like crypto, short-term momentum behaviour often varies between tokens - making diversified, multi-directional exposure a strategic advantage . EQUITY CURVE The STAR framework only updates the underlying realized equity when a position is closed, and the trade outcome is known. This approach ensures: True representation of actual capital available for trading No exposure distortion due to unrealized gains Risk remains tightly linked to realized results This trade-to-trade basis for realized equity modelling eliminates the common pitfall of overallocation based on unrealized profits. The visual equity curve represents an accurate visualization of the Total Equity however, which is equivalent to what would be the realized equity if all trades were closed on the prior bar close. TIMEFRAME CONSIDERATIONS Lower timeframes typically yield better performance for STAR due to: Greater data density per day - more observations = better statistical inference Faster compounding - more trades per week = faster capital rotation However, lower timeframes also suffer from increased slippage and fees. STAR's execution-aware structure helps mitigate this, but users must still choose timeframes appropriate to their liquidity, costs, and operational availability. INPUT OPTIONS Fees (direct trading costs - the percentage of capital removed from the initial position size) Slippage (execution delay, as a percentage. In practice, the fill price is often worse than the signal price. This directly affects R and hence position sizing) Risk % ( Please note : this is the risk level if every position is opened at once. 5% risk for 5 assets is 1% risk per position) System Start date Float Precision value of displayed numbers Table visualization - positioning and table sizes Adjustable color options VISUAL SIMPLICITY To avoid usual unnecessary complexity and empower fast at-a-glance action taking, as well as enable mobile compatibility, only the most relevant information is presented. This includes all information required to open positions in one table. As well as a quick and straightforward overview for the system stats Lastly, there is an optional table that can be enabled displaying more detailed information if desired: USAGE GUIDELINES To use STAR effectively: Input your average slippage and fees % Input your maximum portfolio risk % (this controls overall leverage and is equivalent to the maximum loss that the allocation to STAR would bring if ALL positions are allocated AND hit their stop loss at the same time) Wait for signal alerts with entry, stop, and size details STAR will dynamically calculate sizing, risk exposure, and portfolio allocation on your behalf. Position multipliers, stop placement, and asset-specific risk are all embedded in the system logic. Note: Leverage must be manually set to ISOLATED on your exchange platform to prevent unwanted position linking. ABOUT THE BEAR MARKET DEFENDER STRATEGY The first strategy to launch on the STAR Framework is the BEAR MARKET DEFENDER (BMD) - a fast-acting, trend following system based upon the Trend Titan NEUTRONSTAR. For the details of the logic behind NEUTRONSTAR, please refer to the methodology and trend aggregation section of the following indicator: The BMD ’s short side exit calculation methodology is slightly improved compared to NEUTRONSTAR, to capture downtrends more consistently and also cut positions faster – which is crucial when considering general jump risk in the Crypto space. Accordingly, the only focus of the BMD is to capture trends to the short side, providing the benefit of being in a spectrum from no correlation to being negatively correlated in risk and return behavior to classical Crypto long exposure. More precisely, Crypto behavior showcases that when Bitcoin is in a ranging/mean reverting environment, most tokens that don’t fall into the “Blue-Chip” category tend to find themselves in a trend towards 0. Typically during this period most Crypto portfolios suffer heavily due to a “Crypto-long” biased exposure. The Bear Market Defender thrives in these chaotic, high volatility markets where most coins trend towards zero while the traditional Crypto long exposure is either flat or in a drawdown, therefore the BMD adds a source of uncorrelated risk and returns to hedge typical long exposure and bolster portfolio volatility. Because of the BMD's short-only exposure, it will often suffer small losses during strong uptrends. During these periods, long exposure performs the best and the goal is to outperform the temporary underperformance in the BMD . To take advantage of the abovementioned behavior of most tokens trending to zero, assets traded in the BMD are systematically updated on a quarterly basis with available liquidity being an important consideration for the tokens to be eligible for selection. FINAL SUMMARY The STAR Framework represents a new generation of portfolio grade trading infrastructure, built around disciplined execution, realized equity, and adaptive position sizing. It is designed to support any number of future methodologies - beginning with BMD . The Bear Market Defender is here to hedge out commonly long biased portfolio allocations in the Crypto market, specializing in bringing uncorrelated returns during periods of sideways price action on Bitcoin, or whole-market downturns. Together, STAR + BMD deliver a scalable, volatility tuned system that prioritizes capital preservation, signal accuracy, and adaptive risk allocation. Whether deployed standalone or within a broader portfolio, this framework is engineered for high performance, longevity, and adaptability in the ever-evolving crypto landscape.
Pine Script® göstergesi
QuantraSystems tarafından