EMA20 Anti-Whipsaw Strategy - Clean Entry & Exit LabelsCrypto Strategy named EMA20 Anti-Whipsaw Strategy - Clean Entry & Exit Labels
ابحث في النصوص البرمجية عن "candle"
Estrategia de NY ORB por CPThis strategy marks the New York market opening range during the first 15 minutes and confirms a buy or sell entry once the price returns and retests that range. It’s designed to capture trades of 60 points or more after the range has been retested. I suggest complementing the strategy with an indicator that highlights FVGs (Fair Value Gaps) or order blocks to better understand what price is doing and where it’s heading.
esta estrategia te marca el rango de apertura del mercado de ny de los primeros 15 minutos y te confirma entrada en venta o compra una vez que el precio regrese y retestee el rango. esta diseñada para tener trades de 60 puntos o mas una vez que el rango sea retesteado. sugiero acompañar la estrategia con algun indicador que marque fvg o order blocks para tener una mejor de lo que el precio esta haciendo y hacia donde se dirige.
ORB 15m – First 15min Breakout (Long/Short)ORB 15m – First 15min Breakout (Long/Short)
Apply on SPY, great returns
MomentumSync-PSAR: RSI·ADX Filtered 3-Tier Exit StrategyTriSAR-E3 is a precision swing trading strategy designed to capitalize on early trend reversals using a Triple Confirmation Model. It triggers entries based on an early Parabolic SAR bullish flip, supported by RSI strength and ADX trend confirmation, ensuring momentum-backed participation.
Exits are tactically managed through a 3-step staged exit after a PSAR bearish reversal is detected, allowing gradual profit booking and downside protection.
This balanced approach captures trend moves early while intelligently scaling out, making it suitable for directional traders seeking both agility and control.
Martin Strategy - No Loss Exit v3Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0
Inascript PRO (Elliott + TP System)Inascript PRO (Elliott + TP System) is an intraday strategy for gold (XAUUSD), based on simplified Elliott Wave logic.
It features 3 Take Profits, dynamic Stop Loss, break-even logic, and session filters (London & New York).
Precise alerts include entry, TP, and SL levels.
Developed by Inaskan for clean and smart intraday trading.
LeBlanc Strategy 2 -Inverted Fair Value Gap with Trend & 2.5 RRRThis is for recognizing the closed Inverted Fair Value Gaps (IFVG) to know when to enter a trade.
Detects true inverted FVGs only if the gap size is 3+ ticks.
Filters trades based on EMA50 vs SMA20 trend direction.
Uses ATR-based stop loss, and sets take-profit at a 2.5 risk-to-reward ratio.
Is fully backtestable in TradingView Strategy Tester.
Plots green/red boxes for FVGs.
[PS]Breakout Strategy: Nifty/BN only at 15 min TimeframeIt only works on 15 min timeframe for nifty and Bank nifty.
ICT OTE Strategy Crypto PublicICT OTE Strategy Crypto Public
This strategy automates a classic ICT (Inner Circle Trader) setup specifically tailored for the high-volatility nature of cryptocurrency markets. It aims to enter a trade on a retracement after a confirmed Break of Structure (BOS), using a dual-swing detection method to validate the market's direction before looking for an entry.
The entire process is automated, from identifying the market structure to managing the trade with advanced risk management options. This version uses a percentage of equity for its order sizing, which is ideal for crypto trading.
How It Works
Dual Swing Detection: The strategy uses two different sets of swing strengths to analyze market structure for higher accuracy:
Entry Swings: Weaker, more sensitive swings used to define the immediate dealing range for a potential trade.
Validator Swings: Stronger, more significant swings used to confirm a true Break of Structure.
Break of Structure (BOS): A trade setup is only considered valid after a strong "Validator" swing breaks through a previous "Entry" swing. This confirms the market's intended direction and filters out weak or false moves.
Identify Retracement Leg: After a confirmed BOS, the strategy identifies the most recent "Entry Swing" price leg that led to the break.
Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0).
Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.618), anticipating a price pullback into a discount or premium array.
After a bullish BOS, it looks to BUY the retracement.
After a bearish BOS, it looks to SELL the retracement.
Risk Management:
Stop Loss is placed at the start of the leg (the 1.0 level).
Take Profit is placed at a user-defined level (defaulting to the 0.0 level, with extension options).
Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit.
How to Use
Asset Selection: This strategy is designed for cryptocurrency markets. Its use of percentage-based order sizing is not suitable for tick-based markets like futures.
Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups.
Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Swing Sensitivity" to find the best settings for your specific market and timeframe.
Professional ORB Strategy - BUY & Sell signal- Ganesh SelvarayarORB 15 mins strategy buy and sell signal, with point system for your target
✅ BACKTEST: UT Bot + RSIRSI levels widened (60/40) — more signals.
Removed ATR volatility filter (to let trades fire).
Added inputs for TP and SL using ATR — fully dynamic.
Cleaned up conditions to ensure alignment with market structure.
Multi-TF MACD/RSI Pro Strategy v6How to Use: Timeframe Setup:
Apply to any chart (1s, 5m, 15m)
Set indicator timeframe in settings
Backtesting: Adjust date range in inputs
Check performance in strategy tester
View results in table (top-right corner)
Live Trading: Green triangles = Buy signals
Red triangles = Sell signals
Red lines = Stop loss levels
Green lines = Take profit targets
Test results after 2000 runs on BTC/USD 5m:
// • Win rate: 53.2%
// • Profit factor: 1.87
// • ROI: 27.4% (6 months)
// • Max drawdown: 11.3%
The SamuraiOverview
This strategy implements a session-based range breakout system specifically designed for GBP/JPY trading. The approach focuses on identifying key price ranges during specific market sessions and trading breakouts of these ranges during optimal trading windows. The strategy combines multi-timeframe analysis using 30-minute data with precise session timing to capture high-probability breakout moves.
Entry Logic
The strategy operates on a two-phase approach:
Range Collection Phase:
Monitors price action during a specified session window
Identifies session high and low levels
Only collects ranges on selected trading days
Trading Phase:
Long Entry: Price closes above the established session high
Short Entry: Price closes below the established session low
Entries only occur on valid trading days (day after range collection)
One trade per direction per session to prevent overtrading
Exit Conditions
Stop Loss: Set at a percentage of the session range below entry (long) or above entry (short)
Take Profit: Calculated using a Risk-Reward Ratio based on stop loss distance
Session Close: All positions are closed at the end of the trading window
Risk Management Features
Fixed risk-reward ratio of for consistent risk management
Stop loss calculated as percentage of session range for adaptive sizing
Visual risk/reward boxes display potential outcomes before entry
Daily session close protection prevents overnight exposure
Visual Features
Customizable Colors: Full control over line colors, styles, and box opacities
Risk/Reward Visualization: Color-coded boxes showing potential profit and loss zones
Take Profit Lines: TP level with different line styles for clarity
Stop Loss Line: Clear visual indication of risk level
Clean Interface: Streamlined settings focused on essential visual customization
Important Notes
Timeframe Dependency: Strategy uses 30-minute data regardless of chart timeframe for consistency
Session Timing: All times are in UTC - ensure proper timezone conversion for your location
Trading Days: Default setup trades Tuesday-Friday ranges (Monday-Thursday collection)
Single Position: Only one position per direction per session to maintain discipline
No Pyramiding: Strategy prevents position averaging to maintain clear risk parameters
Suggested Use
Recommended Pairs: Optimized for GBP/JPY but may work on other volatile pairs
Best Timeframes: Display on any timeframe (strategy uses 30m data internally)
Session Awareness: Most effective during high-volatility session transitions
Risk Management: Consider position sizing based on account risk tolerance
Market Conditions: Performs best in trending or breakout market environments
Backtesting Considerations
Strategy includes realistic entry/exit conditions based on closing prices
Visual elements help understand historical performance context
Built-in position management prevents unrealistic results
Session-based logic ensures trades align with actual market sessions
This strategy is designed for traders who prefer systematic, rule-based approaches to breakout trading with clear risk management parameters. The visual feedback helps in understanding market context and decision-making process.
Disclaimer: Past performance does not guarantee future results. Always test thoroughly on historical data and consider your risk tolerance before live trading.
🔥 HYBRID SCALPING Bot - เข้าง่าย ออกแม่นA tool bot that helps analyze charts accurately, focusing on profits.
StarStrat Ceres Strategy [0.3.1]2025ETH 30M Composite Golden Indicator Trend Strategy
This strategy is designed for Ethereum 30-minute timeframe, utilizing composite golden indicators combined with trend indicators for trade signal identification.
Trading Logic:
- Entry: Triggered when composite golden indicator and trend indicator confirm same direction
- Exit: Partial profit-taking mechanism with customizable parameters for each position
- Risk Management: Built-in risk coefficient, recommended setting at 1%
All key parameters are adjustable to adapt to different trading styles.
Risk Disclaimer: For educational and research purposes only. Not investment advice. Cryptocurrency trading involves high risk, please trade cautiously.
Buy The Dip - ENGThis script implements a grid trading strategy for long positions in the USDT market. The core idea is to place a series of buy limit orders at progressively lower prices below an initial entry point, aiming to lower the average entry price as the price drops. It then aims to exit the entire position when the price rises a certain percentage above the average entry price.
Here's a detailed breakdown:
1. Strategy Setup (`strategy` function):
`'거미줄 자동매매 250227'`: The name of the strategy.
`overlay = true`: Draws plots and labels directly on the main price chart.
`pyramiding = 15`: Allows up to 15 entries in the same direction (long). This is essential for grid trading, as it needs to open multiple buy orders.
`initial_capital = 600`: Sets the starting capital for backtesting to 600 USDT.
`currency = currency.USDT`: Specifies the account currency as USDT.
`margin_long/short = 0`: Doesn't define specific margin requirements (might imply spot trading logic or rely on exchange defaults if used live).
`calc_on_order_fills = false`: Strategy calculations happen on each bar's close, not just when orders fill.
2. Inputs (`input`):
Core Settings:
`lev`: Leverage (default 10x). Used to calculate position sizes.
`Investment Percentage %`: Percentage of total capital to allocate to the initial grid (default 80%).
`final entry Percentage %`: Percentage of the *remaining* capital (100 - `Investment Percentage %`) to use for the "semifinal" entry (default 50%). The rest goes to the "final" entry.
`Price Adjustment Length`: Lookback period (default 4 bars) to determine the initial `maxPrice`.
`price range`: The total percentage range downwards from `maxPrice` where the grid orders will be placed (default -10%, meaning 10% down).
`tp`: Take profit percentage above the average entry price (default 0.45%).
`semifinal entry price percent`: Percentage drop from `maxPrice` to trigger the "semifinal" larger entry (default -12%).
`final entry price percent`: Percentage drop from `maxPrice` to trigger the "final" larger entry (default -15%).
Rounding & Display:
`roundprice`, `round`: Decimal places for rounding price and quantity calculations.
`texts`, `label_style`: User interface preferences for text size and label appearance on the chart.
Time Filter:
`startTime`, `endTime`: Defines the date range for the backtest.
3. Calculations & Grid Setup:
`maxPrice`: The highest price point for the grid setup. Calculated as the lowest low of the previous `len` bars only if no trades are open. If trades are open, it uses the entry price of the very first order placed in the current sequence (`strategy.opentrades.entry_price(0)`).
`minPrice`: The lowest price point for the grid, calculated based on `maxPrice` and `range1`.
`totalCapital`: The amount of capital (considering leverage and `per1`) allocated for the main grid orders.
`coinRatios`: An array ` `. This defines the *relative* size ratio for each of the 11 grid orders. Later orders (at lower prices) will be progressively larger.
`totalRatio`: The sum of all ratios (66).
`positionSizes`: An array calculated based on `totalCapital` and `coinRatios`. It determines the actual quantity (size) for each of the 11 grid orders.
4. Order Placement Logic (`strategy.entry`):
Initial Grid Orders:
Runs only if within the specified time range and no position is currently open (`strategy.opentrades == 0`).
A loop places 11 limit buy orders (`Buy 1` to `Buy 11`).
Prices are calculated linearly between `maxPrice` and `minPrice`.
Order sizes are taken from the `positionSizes` array.
Semifinal & Final Entries:
Two additional, larger limit buy orders are placed simultaneously with the grid orders:
`semifinal entry`: At `maxPrice * (1 - semifinal / 100)`. Size is based on `per2`% of the capital *not* used by the main grid (`1 - per1`).
`final entry`: At `maxPrice * (1 - final / 100)`. Size is based on the remaining capital (`1 - per2`% of the unused portion).
5. Visualization (`line.new`, `label.new`, `plot`, `plotshape`, `plotchar`):
Grid Lines & Labels:
When a position is open (`strategy.opentrades > 0`), horizontal lines and labels are drawn for each of the 11 grid order prices and the "final" entry price.
Lines extend from the bar where the *first* entry occurred.
Labels show the price and planned size for each level.
Dynamic Coloring: If the price drops below a grid level, the corresponding line turns green, and the label color changes, visually indicating that the level has been reached or filled.
Plotted Lines:
`maxPrice` (initial high point for the grid).
`strategy.position_avg_price` (current average entry price of the open position, shown in red).
Target Profit Price (`strategy.position_avg_price * (1 + tp / 100)`, shown in green).
Markers:
A flag marks the `startTime`.
A rocket icon (`🚀`) appears below the bar where the `final entry` triggers.
A stop icon (`🛑`) appears below the bar where the `semifinal entry` triggers.
6. Exit Logic (`strategy.exit`, `strategy.entry` with `qty=0`):
Main Take Profit (`Full Exit`):
Uses `strategy.entry('Full Exit', strategy.short, qty = 0, limit = target2)`. This places a limit order to close the entire position (`qty=0`) at the calculated take profit level (`target2 = avgPrice * (1 + tp / 100)`). Note: Using `strategy.entry` with `strategy.short` and `qty=0` is a way to close a long position, though `strategy.exit` is often clearer. This exit seems intended to apply whenever any part of the grid position is open.
First Order Trailing Stop (`1st order Full Exit`):
Conditional: Only active if `trail` input is true AND the *last* order filled was "Buy 1" (meaning only the very first grid level was entered).
Uses `strategy.exit` with `trail_points` and `trail_offset` based on ATR values to implement a trailing stop loss/profit mechanism for this specific scenario.
This trailing stop order is cancelled (`strategy.cancel`) if any subsequent grid orders ("Buy 2", etc.) are filled.
Final/Semifinal Take Profit (`final Full Exit`):
Conditional: Only active if more than 11 entries have occurred (meaning either the "semifinal" or "final" entry must have triggered).
Uses `strategy.exit` to place a limit order to close the entire position at the take profit level (`target3 = avgPrice * (1 + tp / 100)`).
7. Information Display (Tables & UI Label):
`statsTable` (Top Right):
A comprehensive table displaying grouped information:
Market Info (Entry Point, Current Price)
Position Info (Avg Price, Target Price, Unrealized PNL $, Unrealized PNL %, Position Size, Position Value)
Strategy Performance (Realized PNL $, Realized PNL %, Initial/Total Balance, MDD, APY, Daily Profit %)
Trade Statistics (Trade Count, Wins/Losses, Win Rate, Cumulative Profit)
`buyAvgTable` (Bottom Left):
* Shows the *theoretical* entry price and average position price if trades were filled sequentially up to each `buy` level (buy1 to buy10). It uses hardcoded percentage drops (`buyper`, `avgper`) based on the initial `maxPrice` and `coinRatios`, not the dynamically changing actual average price.
`uiLabel` (Floating Label on Last Bar):
Updates only on the most recent bar (`barstate.islast`).
Provides real-time context when a position is open: Size, Avg Price, Current Price, Open PNL ($ and %), estimated % drop needed for the *next* theoretical buy (based on `ui_gridStep` input), % rise needed to hit TP, and estimated USDT profit at TP.
Shows "No Position" and basic balance/trade info otherwise.
In Summary:
This is a sophisticated long-only grid trading strategy. It aims to:
1. Define an entry range based on recent lows (`maxPrice`).
2. Place 11 scaled-in limit buy orders within a percentage range below `maxPrice`.
3. Place two additional, larger buy orders at deeper percentage drops (`semifinal`, `final`).
4. Calculate the average entry price as orders fill.
5. Exit the entire position for a small take profit (`tp`) above the average entry price.
6. Offer a conditional ATR trailing stop if only the first order fills.
7. Provide extensive visual feedback through lines, labels, icons, and detailed information tables/UI elements.
Keep in mind that grid strategies can perform well in ranging or slowly trending markets but can incur significant drawdowns if the price trends strongly against the position without sufficient retracements to hit the take profit. The leverage (`lev`) input significantly amplifies both potential profits and losses.
Aether SignalAether Signal is a professional TradingView indicator engineered for advanced traders who demand precise analysis, smart money concepts, and robust risk management. It systematically incorporates institutional trading techniques, automated level detection, and multi-level profit-taking for exceptional trade execution.
Support & Resistance: Aether Signal automatically identifies key support and resistance levels using mathematically rigorous algorithms, ensuring that traders see the most significant price barriers for their entries and exits.
Smart Money Concepts: The indicator is grounded in institutional trading logic, analyzing market structure to pinpoint where large market participants are engaging. It leverages volume and price interaction at critical zones, similar to harmonic liquidity nodes in professional strategies.
Precise Entry Points: Entry signals are generated when strict confluence conditions are met, ensuring signals align with underlying market structure, high-volume footprints, and optimal momentum. Stops are logically placed just beyond the validated support or resistance—on the opposite side of the key zone.
Triple Take Profits: Aether Signal equips traders to maximize returns with three intelligently placed take profit levels (TP1, TP2, TP3), allowing for strategic scaling out and adaptive trade management.
Supply & Demand Zones: The indicator scans for market imbalances by identifying high-probability supply and demand areas driven by institutional activity and volume anomalies, guiding traders toward potent reversal or continuation setups.
Advanced Risk Management: Robust risk controls are integrated, including logical stop loss suggestions and trade selection filters, to minimize overtrading and enhance consistency.
Win Rate: The system claims a win rate of up to 96% under optimal settings and strict adherence to its entry criteria, setting a high benchmark for performance (note: actual results may vary depending on market conditions and trader discipline).
Aether Signal is tailored for traders seeking the edge of institutional-grade analytics—offering comprehensive structure analysis, actionable alerts, and performance-focused features that merge automation with trader control.
Refined MA + Engulfing (M5 + Confirmed Structure Break)I would like to start by saying that this strategy was put together using ChatGPT, some past trades from myself and some backtested trades, and from my time as a student in Wallstreet Academy under Cue Banks.
I am not profitable yet. I am too jumpy and blow accounts. I'm hoping this strategy (and it's indicator twin) can help me spend less time on the charts, so that I'm not tempted to press buttons as much.
It does fire quite a bit. But, the Strategy Tester tab shows a 30% win rate with our wins being significant to our losses. So, in theory, if you followed the rules of this strategy STRICTLY, you COULD BE profitable.
With that being said, there are times that this strategy has shown to trigger and I ask, "Why?".
I just want to help myself and others, and maybe make some decent\cool stuff along the way. Enjoy
KR
Swing FX Pro Panel v1Description:
"Swing FX Pro Panel v1" is a professional swing trading strategy tailored for the Forex market and other highly liquid assets. The core logic is based on the crossover of two Exponential Moving Averages (EMA), allowing the strategy to detect trend shifts and generate precise entry signals.
The script includes an interactive performance panel that dynamically displays:
initial capital,
risk per trade (%),
the number of trades taken during a selected period (e.g., 6 months),
win/loss statistics,
ROI (Return on Investment),
maximum drawdown,
win ratio.
Pullback Pro Dow Strategy v7 (ADX Filter)
### **Strategy Description (For TradingView)**
#### **Title:** Pullback Pro: Dow Theory & ADX Strategy
---
#### **1. Summary**
This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities.
To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum.
---
#### **2. Core Logic: How It Works**
The strategy's logic is broken down into three main steps:
**Step 1: Trend Determination (Dow Theory)**
* The primary trend is identified by analyzing recent pivot points.
* An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL).
* A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL).
* If neither pattern is present, the strategy considers the market to be in a range and will not seek trades.
**Step 2: Entry Signal (Pullback to EMA)**
* Once a clear trend is established, the strategy waits for a price correction.
* **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA.
* **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA.
**Step 3: Confirmation & Risk Management**
* **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets.
* **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point:
* For long trades, it's placed at the `lastPivotLow`.
* For short trades, it's placed at the `lastPivotHigh`.
* **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2).
---
#### **3. Input Settings Explained**
**① Dow Theory Settings**
* **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots.
**② Entry Logic (Pullback)**
* **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries.
**③ Risk & Exit Management**
* **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target.
* **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit.
* **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target.
**④ Filters**
* **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter.
* **ADX Length:** The lookback period for the ADX calculation.
* **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level.
---
#### **4. Best Practices & Recommendations**
* This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior.
* It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect.
* **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application.
* Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics.
---
#### **DISCLAIMER**
This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description
Overview
The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes.
Performance Highlight:
In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior.
The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well.
## Key Innovation & Originality
This strategy introduces a unique **dual scoring system** approach:
- **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria
- **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing
Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions.
## Technical Foundation
### Optimized Indicator Parameters
The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns:
**MACD Configuration (3,10,3)**:
- Fast EMA: 3 periods (vs standard 12)
- Slow EMA: 10 periods (vs standard 26)
- Signal Line: 3 periods (vs standard 9)
- **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility
**RSI Configuration (21-period)**:
- Length: 21 periods (vs standard 14)
- Oversold: 30 level
- Extreme Oversold: 25 level
- **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment
**Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance.
### Scoring System Methodology
**Entry Score Components (Minimum 13 points required)**:
1. **RSI Signals** (max 5 points):
- RSI < 30: +2 points
- RSI < 25: +2 points
- RSI turning up: +1 point
2. **MACD Signals** (max 8 points):
- MACD below zero: +1 point
- MACD turning up: +2 points
- MACD histogram improving: +2 points
- MACD bullish divergence: +3 points
3. **Price Action** (max 4 points):
- Long lower wick (>50%): +2 points
- Small body (<30%): +1 point
- Bullish close: +1 point
4. **Pattern Recognition** (max 8 points):
- RSI bullish divergence: +4 points
- Quick recovery pattern: +2 points
- Reversal confirmation: +4 points
**Exit Score Components (Minimum 13 points required)**:
Uses inverse criteria to identify swing tops with similar weighting system.
## Risk Management Features
### Position Sizing & Risk Control
- **Single Position Strategy**: 100% equity allocation per trade
- **No Overlapping Positions**: Ensures focused risk management
- **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets
### Stop Loss & Take Profit Logic
- **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer
- **Risk-Based Take Profit**: Calculated using risk/reward ratio
- **Clean Exit Logic**: Prevents conflicting signals
## Default Settings Optimization
### Key Parameters (Optimized for MSTR/Bitcoin-style volatility):
- **Minimum Entry Score**: 13 (ensures high-conviction entries)
- **Minimum Exit Score**: 13 (prevents premature exits)
- **Risk/Reward Ratio**: 5.0 (accounts for volatility)
- **Lower Wick Threshold**: 50% (identifies true hammer patterns)
- **Divergence Lookback**: 8 bars (optimal for swing timeframes)
### Why These Defaults Work for MSTR:
1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation
2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets
3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks
4. **21-period RSI**: Reduces noise while maintaining sensitivity
## Visual Features
### Score Display System
- **Green Labels**: Entry scores ≥10 points (below bars)
- **Red Labels**: Exit scores ≥10 points (above bars)
- **Large Triangles**: Actual trade entries/exits
- **Small Triangles**: Reversal pattern confirmations
### Chart Cleanliness
- Indicators plotted in separate panes (MACD, RSI)
- TP/SL levels shown only during active positions
- Clear trade markers distinguish signals from actual trades
## Backtesting Specifications
### Realistic Trading Conditions
- **Commission**: 0.1% per trade
- **Slippage**: 3 points
- **Initial Capital**: $1,000
- **Account Type**: Cash (no margin)
### Sample Size Considerations
- Strategy designed for 100+ trade sample sizes
- Recommended timeframes: 4H, 1D for swing trading
- Optimal for trending/volatile markets
## Strategy Limitations & Considerations
### Market Conditions
- **Best Performance**: Trending markets with clear swings
- **Reduced Effectiveness**: Highly choppy, sideways markets
- **Volatility Dependency**: Optimized for moderate to high volatility assets
### Risk Warnings
- **High Allocation**: 100% position sizing increases risk
- **No Diversification**: Single position strategy
- **Backtesting Limitation**: Past performance doesn't guarantee future results
## Usage Guidelines
### Recommended Assets & Timeframes
- **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes
- **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.)
- **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments)
- **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping
### Timeframe Recommendations
- **Primary Scalping**: 5-minute and 15-minute charts
- **Active Monitoring**: 1-minute for precise entries
- **Swing Scalping**: 30-minute to 1-hour timeframes
- **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities)
## Technical Requirements
- **Pine Script Version**: v6
- **Overlay**: Yes (plots on price chart)
- **Additional Panes**: MACD and RSI indicators
- **Real-time Compatibility**: Confirmed bar signals only
## Customization Options
All parameters are fully customizable through inputs:
- Indicator lengths and levels
- Scoring thresholds
- Risk management settings
- Visual display preferences
- Date range filtering
## Conclusion
This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets.
The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets.
**Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
Grid TLong V1The “Grid TLong V1” strategy is based on the classic Grid strategy, but in the mode of buying and selling in favor of the trend and only on Long. This allows to take advantage of large uptrend movements to maximize profits in bull markets. For this reason, excessively sideways or bearish markets may not be very conducive to this strategy.
Like our Grid strategies in favor of the trend, you can enter and exit with the balance with controlled risk, as the distance between each grid functions as a natural and adaptable stop loss and take profit. What differentiates it from bidirectional strategies is that Short uses a minimum amount of follow-through, so that the percentage distance between the grids is maintained.
In this version of the script the entries and exits can be chosen at market or limit , and are based on the profit or loss of the current position, not on the percentage change in price.
The user may also notice that the strategy setup is risk-controlled, because it risks 5% on each trade, has a fairly standard commission and modest initial capital, all in order to protect the strategy user from unrealistic results.
As with all strategies, it is strongly recommended to optimize the parameters for the strategy to be effective for each asset and for each time frame.
