Long and Short Strategy with Multi Indicators [B1P5]Long and Short Strategy with RSI, ROC, MA Selection, Exit Visualization, and Strength Indicator
Análisis de tendencia
Supertrend Long-Only Strategy for QQQThis strategy is meant to use Micro Momentum to give good Buy and Sell signals in trending markets
NOMANOMA Adaptive Confidence Strategy —
What is NOMA?
NOMA is a next-generation, confidence-weighted trading strategy that fuses modern trend logic, multi-factor market structure, and adaptive risk controls—delivering a systematic edge across futures, stocks, forex, and crypto markets. Designed for precision, adaptability, and hands-off automation, NOMA provides actionable trade signals and real-time alerts so you never miss a high-conviction opportunity.
Key Benefits & Why Use NOMA?
Trade With Confidence, Not Guesswork:
NOMA combines over 11 institutional-grade confirmations (market structure, order flow, volatility, liquidity, SMC/ICT concepts, and more) into a single “confidence score” engine. Every trade entry is filtered through customizable booster weights, so only the strongest opportunities trigger.
Built-In Alerts:
Get instant notifications on all entries, take-profits, trailing stop events, and exits. Connect alerts to your mobile, email, or webhook for seamless automation or just peace of mind.
Advanced Position Management:
Supports up to 5 separate take-profit levels with adjustable quantities, plus dynamic and stepwise trailing stops. Protects your gains and adapts exit logic to market movement, not just static targets.
Anti-Chop/No Trade Zones:
Eliminate low-probability, sideways market conditions using the “No Chop Zone” filter, so you only trade in meaningful, trending environments.
Full Market Session Control:
Restrict trades to custom sessions (e.g., New York hours) for added discipline and to avoid overnight risk.
— Ideal for day traders and prop-firm requirements.
Multi-Asset & Timeframe Support:
Whether you trade micro futures, stocks, forex, or crypto, NOMA adapts its TP/SL logic to ticks, pips, or points and works on any timeframe.
How NOMA Works (Feature Breakdown)
1. Adaptive Trend Engine
Uses a custom NOMA line that blends classic moving averages with dynamic momentum and a proprietary “Confidence Momentum Oscillator” overlay.
Visual trend overlay and color fill for easy chart reading.
2. Multi-Factor Confidence Scoring
Each trade is scored on up to 11 confidence “boosters,” including:
Market Manipulation & Accumulation (detects smart money traps and true range expansions)
Accumulation/Distribution (AD line)
ATR Volatility Rank (prioritizes trades when volatility is “just right”)
COG Cross (center of gravity reversal points)
Change of Character/Break of Structure (CHoCH/BOS logic, SMC/ICT style)
Order Blocks, Breakers, FVGs, Inducements, OTE (Optimal Trade Entry) Zones
You control the minimum score required for a trade to trigger, plus the weight of each factor (customize for your asset or style).
3. Smart Trade Management
Step Take-Profits:
Up to 5 profit targets, each with individual contract/quantity splits.
Step Trailing Stop:
Trail your stop with a ratcheting logic that tightens after each TP is hit, or use a fully dynamic ATR-based trail for volatile markets.
Kill-Switch:
Instant trailing stop logic closes all open contracts if price reverses sharply.
4. Session Filter & Cooldown Logic
Restricts trading to key sessions (e.g., NY open) to avoid low-liquidity or dead zones.
Cooldown bars prevent “overtrading” or rapid re-entries after an exit.
5. Chop Zone Filter
Optionally blocks trades during flat/choppy periods using a custom “NOMA spread” calculation.
When enabled, background color highlights no-trade periods for clarity.
6. Real-Time Alerts
Receive alerts for:
Trade entries (long & short, with confidence score)
Every take-profit target hit
Trailing stop exits or full position closes
Easy setup: Create alerts for all conditions and get notified instantly.
Customization & Inputs
TP/SL Modes: Choose between manual, ATR-multiplied, or hybrid take-profit and trailing logic.
Position Sizing: Fixed contracts/quantity per trade, with customizable splits for scaling out.
Session Settings: Restrict to any time window.
Confidence Engine: User-controlled weights and minimum score—tailor for your asset.
Risk & Volatility Filters: ATR length/multiplier, min/max range, and more.
How To Use
Add NOMA to your chart.
Customize your settings (session, TPs, confidence scores, etc.).
Set up TradingView alerts (“Any Alert() function call”) to receive notifications.
Monitor trade entries, profit targets, and stops directly on your chart or in your inbox.
Adjust confidence weights as you optimize for your favorite asset.
Pro Tips
Start with default settings—they are optimized for NQ micro futures, 15m timeframe.
Increase the minimum confidence score or weights for stricter filtering in volatile or low-liquidity markets.
Adjust your take-profit and trailing stop settings to match your trading style (scalping vs. swing).
Enable “No Chop Zone” during sideways conditions for cleaner signals.
Test in strategy mode before trading live to dial in your risk and settings.
Disclaimer
This script is for educational and research purposes only. No trading system guarantees future results.
Performance will vary by symbol, timeframe, and market regime—always test settings and use at your own risk. Not investment advice.
If alerts or strategy entries are not triggering as expected, try lowering the minimum confidence score or disabling certain boosters.
This will come with a user manual please do not hesitate to message me to gain access. TO THE MOON AND BEYOND
Tri-Monthly BTC Swing StrategyWhat This Does:
Component Function
EMA200 Filters long-term bullish conditions
MACD crossover Confirms swing entry
RSI > 50 Confirms momentum is strong
90-day cooldown Ensures you're not overtrading
Exit on MACD/RSI weakness Protects from reversals
Ponelope v1.4 | Flow with the TrendThis strategy seeks precision long entries during structurally confirmed uptrends, leveraging multi-timeframe moving averages to align market context. Entry signals trigger only after price experiences a tactical pullback within an otherwise bullish regime—capturing value during temporary weakness rather than chasing highs.
A local trend is validated via a simple moving average, while a higher-timeframe confirmation ensures macro alignment. Stops are governed by a fallback volatility-based level, and exits are enforced upon trend deterioration, reducing exposure to sharp reversals. The result is a durable, context-aware system that adapts across market cycles and emphasizes capital protection while seeking asymmetric reward setups.
CE XAU/USDT Strategy📌 Auto-Trading Strategy Using CE on XAU/USDT (5M)
Indicator: CE
Parameters:
• ATR Period: 1
• ATR Multiplier: 1.85
Timeframe: 5 minutes
Instrument: Gold (XAU/USD)
🔁 Logic:
• Buy signal → Close short, open long
• Sell signal → Close long, open short
⚙️ Automation:
1. CE indicator on TradingView generates signals
2. Signals are sent via webhook to a Python bot
3. The bot opens/closes trades in MT5 accordingly
✅ Advantages:
• Full automation
• Operates 24/7 without manual intervention
⚠️ Important:
• Always test on a demo account
• Manage risk and position size properly
📌 Стратегия автоторговли по CE на XAU/USDT (5М)
Индикатор: CE
Параметры:
• ATR Period: 1
• ATR Множитель: 1.85
Таймфрейм: 5 минут
Инструмент: Золото (XAU/USD)
🔁 Логика:
• Buy сигнал → закрыть шорт, открыть лонг
• Sell сигнал → закрыть лонг, открыть шорт
⚙️ Автоматизация:
1. CE в TradingView генерирует сигналы
2. Webhook отправляет их в Python-бот
3. Бот открывает/закрывает сделки в MT5
✅ Плюсы:
• Полная автоматизация
• Работа 24/7 без вмешательства
⚠️ Важно:
• Тестируй на демо
• Управляй рисками и лотами
粽子趋势波段策略应用在一小时图表上，提示做多或做空信号，注意⚠️每个信号只作为独立的进场信号，止盈止损自己把握，如做多信号出来之后，可进场做多，止盈止损自己把握，当做空信号出来后并不是前面做多信号的止盈信号，而是独立的新的做空信号，所以止盈止损需自己把握。
本策略适用于加密货币，外汇黄金，股票，期货，指数，作为运用在一小时图表上的做多做空进场信号提示。
联系作者，微：bbm_im7
Applied on the one-hour chart, prompting the long or short signal, note ⚠️ Each signal is only used as an independent entry signal, and the take-profit stop loss is grasped by yourself. For example, after the long signal comes out, you can enter the market and make a long, and the take-profit stop loss is grasped by yourself. When the short signal comes out, it is not the take-profit signal of the previous long signal, but independent The new short-sal signal, so you need to grasp the take-profit and stop-loss by yourself.
This strategy is applicable to cryptocurrencies, foreign exchange gold, stocks, futures, indexes, and is used as a signal prompt to enter the market on the one-hour chart.
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.
J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)📈 J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)
Version: Pine Script v6
Author: Thomas Lee
Category: Trend-Following / Mean Reversion / Scalping
Timeframes: Optimized for 1–5m (but adaptable) Seems to work best on Fibb Time
🧠 Strategy Overview:
The J-Lines Ribbon 4-Cycle Engine is a precision trading algorithm designed to navigate complex market microstructure across four adaptive states:
🔁 CHOP (No Trade / Flatten)
🟡 ANTI (Legacy Layer / Under Development)
🟢 LONG (Trend-Continuation & Rebounds)
🔴 SHORT (Inverse Trend-Continuation & Rebounds)
It combines a multi-layer EMA ribbon, ADX-based CHOP detection, and smart pivot analysis to dynamically shift between market modes, entering and exiting trades with surgical precision.
🔍 Core Features:
Dynamic Market Cycle Detection
Auto-classifies each bar into one of the 4 market states using ADX + EMA 72/89 crossovers.
One-Shot Entries & Rebound Logic
Initiates base entries at the start of new trend cycles. Re-entries (ReLong/ReShort) trigger on EMA 72 and EMA 126 pullbacks with momentum resumption.
CHOP State Autopilot
Automatically closes open positions when CHOP begins, preventing sideways market exposure.
Precision Take-Profits & Pivots-Based Stop Losses
Real-time adaptive exits using pivot high/low swing points as dynamic SL/TP anchors.
Customizable Parameters
Pivot length (left/right)
ADX thresholds
Rebound tolerance bands
Ribbon display and state-labels
📊 Indicator Components:
📏 EMA Ribbon: 72, 89, 126, 267, 360, 445
📉 ADX Filter: Filters out sideways noise, confirms directional bias
🔁 Crossover Events: Detects trend initiations
🌀 Cycle Labels: Real-time visual display of current market state
🛠️ Ideal Use Cases:
Scalping volatile markets
Automated strategy testing & optimization
Entry/exit signal confirmation for discretionary traders
Trend filtering in algorithmic stacks
⚠️ Notes:
ANTI cycle logic is scaffolded but not fully deployed in this version. It will be extended in a future release for deep mean-reversion detection.
Tailor ADX floor and pivot sensitivity to your specific asset and timeframe for optimal performance.
Gentlewhale TQQQ SMA LongBuy and hold TQQQ when price is above 200 SMA 5%, close when price is below 200 SMA 1%.
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
Valdes Trading Bots – 6H AutomationValdes Trading Bots – 6H Automation
This strategy is designed for 6-hour charts and applies structured logic to identify potential long and short entries. It operates with fixed internal rules and does not rely on user-adjusted inputs for decision-making.
Core Functionality:
Uses volatility-based entry conditions to trigger directional trades
Supports two entries per direction using pyramiding
Applies layered take profit levels to scale out of positions
Includes breakeven and trailing stop logic to reduce downside risk
Configurable comments for long and short entries to support alert workflows
Execution Notes:
Non-repainting and non-optimized design
No reliance on future data or external variables
Intended for backtesting and alert integration on 6H timeframes
Performance Characteristics:
Backtesting over a wide range of assets shows:
High win-rate behavior across multiple market types
Strong trade frequency and positive risk-to-reward balance
Consistent equity growth with defined drawdown limits
This script is meant for educational and development purposes and should be tested thoroughly in simulated environments before applying to any live scenario.
PRO Investing - Quant AlphaCentauri D |XLF|PRO Investing - Quant AlphaCentauri D |XLF|
1. Summary and Core Concept
This is a quantitative backtesting strategy engineered specifically for the Financial Select Sector SPDR Fund (XLF) on the Daily (1D) timeframe. The name "AlphaCentauri" reflects its goal: to seek alpha by identifying statistically significant opportunities through rigorous time series analysis.
The strategy's core principle is to move beyond conventional technical indicators and instead analyze the underlying structure and character of price data. It is designed to methodically identify conditions that have historically preceded sustained directional trends in the financial sector.
2. The Analytical Process: How It Works
This strategy employs a multi-stage quantitative process to filter for high-probability setups. It is a "mashup" of statistical concepts applied to price action.
Structural Pattern Recognition: The engine's primary function is to analyze the historical price series of XLF to identify specific, recurring structural patterns. It examines price geometry and cyclical behavior to find formations that often act as the foundation for a new, emerging trend.
Signal Execution: A signal to enter a trade is only generated when the findings from both the structural analysis and the validation stages are in agreement. This disciplined, multi-layered approach ensures the strategy remains flat during periods of high uncertainty and only engages when its quantitative criteria are fully met.
3. How to Use This Strategy
Timeframe: This strategy has been designed, tested, and optimized exclusively for the Daily (1D) timeframe on the XLF ticker. Its logic is not intended for other timeframes or assets and may produce unreliable results if used differently.
On-Chart Signals: The strategy's operation is transparent. It plots all historical buy and sell entries, along with their corresponding exits, directly on the chart for easy performance review and analysis.
4. Risk Management: The Strategy's Foundation
This strategy is built upon a foundation of strict, non-negotiable risk management, which is reflected in its code and backtesting parameters. This design complies with TradingView's guidelines for publishing realistic and responsible strategies.
Dynamic Stop-Loss and Position Sizing: A stop-loss is dynamically calculated for each trade based on recent market volatility. The strategy then automatically adjusts the position size for that trade to target a defined risk percentage. In cases of extreme market volatility, the maximum potential loss on a single trade may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, the risk for most trades will be below this maximum threshold.
Realistic Backtesting Parameters:
Initial Capital: The backtest defaults to an initial capital of $100,000.
Commission: A realistic fee of $5.00 per order is included to simulate broker costs.
5. Disclaimer
This strategy is an educational tool provided for informational and research purposes. It is not financial advice. All trading carries a high level of risk, and past performance is not a guarantee of future results. You are solely responsible for your own trading decisions and risk management. Always conduct your own due diligence before deploying any trading strategy in a live account.
HSI1! First 30m Candle Strategy (15m Chart)## HSI1! First 30-Minute Candle Breakout Strategy (15m Chart) — Description
### Overview
This strategy is designed for trading **Hang Seng Index (HSI) Futures** on a 15-minute chart. It uses the price range established during the first 30 minutes of the Hong Kong main session (09:15–09:44:59) to define key breakout levels for a systematic trade entry each day.
### How the Strategy Works
#### 1. Reference Candle Period
- **Aggregation Window:** The strategy monitors the first two 15-minute bars of the session (09:15:00–09:44:59 HKT).
- **Range Capture:** It records the highest and lowest prices (the "reference high/low") during this window.
#### 2. Trade Setup
- After the 09:45 bar completes, the reference range is locked in.
- Throughout the rest of the trading day (within session hours), the strategy looks for breakouts beyond the reference range.
#### 3. Entry Rules
- **Long Entry (Buy):**
- Triggered if price rises to or above the reference high.
- Only entered if the user's settings permit "Buy Only" or "Both".
- **Short Entry (Sell):**
- Triggered if price falls to or below the reference low.
- Only entered if the user's settings permit "Sell Only" or "Both".
- **Single trade per day:**
- Once any trade executes, no additional trades are opened until the next session.
#### 4. Exit Rules
- **Take Profit (TP):**
- Target profit is set to a distance equal to the initial range added above the long entry (or subtracted below the short entry).
- Example: For a 100-point range, a long trade targets entry + 100 points.
- **Stop Loss (SL):**
- Longs are stopped out if price falls back to the session's reference low; shorts are stopped out if price rallies to the reference high.
#### 5. Session Control
- Active only within the regular day session (09:15–12:00 and 13:00–16:00 HKT).
- Trade tracking resets each new trading day.
#### 6. Trade Direction Manual Setting
- A user input allows restriction to "Buy Only", "Sell Only" or "Both" directions, providing discretion over daily bias.
### Example Workflow
| Step | Action |
|---------------------------|-------------------------------------------------------------------------|
| 09:15–09:44 | Aggregate first two 15m candles; record daily high/low |
| After 09:45 | Wait for a breakout (price crossing either the high or the low) |
| Long trade triggered | Enter at the reference high, target is "high + range", SL is at the low |
| Short trade triggered | Enter at the reference low, target is "low - range", SL at the high |
| Trade management | No more trades for the day, regardless of further breakouts |
| End of session (if open) | Trades may be closed per further logic or left to strategy to handle |
### Key Features and Benefits
- **Discipline:** Only one trade per day, minimizing overtrading.
- **Clarity:** Transparent entry/exit rules; no discretionary execution.
- **Flexibility:** User can bias system to buy-only, sell-only, or allow both, depending on trend or personal view.
- **Simple Risk Control:** Pre-defined stop loss and profit target for every trade.
- **Works best in:** Trending, breakout-prone markets with a history of impulsive moves early in the session.
This strategy is ideal for systematic traders looking to capture the Hang Seng's early session momentum, with robust rule-based management and minimal intervention.
HSI First 30m Candle Strategy (5m Chart)## HSI First Candle Breakout Strategy
USE on 10m TF for max profit rate.
**The HSI First Candle Breakout Strategy** is a systematic trading approach tailored for Hang Seng Index Futures during the main Hong Kong day session. The strategy is designed to capture early market momentum by reacting to the first significant move of the day.
### How It Works
- **Reference Candle:** At the start of each day session (09:00), the high and low of the first 15-minute candle are recorded.
- **Breakout Trigger:**
- A **buy (long) trade** is initiated if price breaks above the first candle’s high.
- A **sell (short) trade** is initiated if price breaks below the first candle’s low.
- **Stop Loss & Take Profit:**
- Stop-loss is placed on the opposite side of the reference candle.
- Take-profit target is set at a distance equal to the size of the reference candle (1R).
- **Filters:**
- Skip the day if the first candle’s range exceeds 200 index points.
- Only the first triggered direction is traded per session.
- All trades are closed before the market closes if neither target nor stop is hit.
- **Execution:** The strategy works best on intraday charts (5m or 15m) and is ideal for traders seeking disciplined, systematic intraday setups.
### Key Features
- Captures the day’s initial momentum burst.
- Strict risk management with predefined stops and targets.
- One trade per day, reducing overtrading and noise.
- Clear-cut, rule-based, and objective system—no discretion required.
**This strategy offers a transparent and robust framework for traders to systematically capture high-probability breakouts in the Hang Seng Index Futures market.**
LANZ Strategy 6.0 [Backtest]🔷 LANZ Strategy 6.0 — Precision Backtesting Based on 09:00 NY Candle, Dynamic SL/TP, and Lot Size per Trade
LANZ Strategy 6.0 is the simulation version of the original LANZ 6.0 indicator. It executes a single LIMIT BUY order per day based on the 09:00 a.m. New York candle, using dynamic Stop Loss and Take Profit levels derived from the candle range. Position sizing is calculated automatically using capital, risk percentage, and pip value — allowing accurate trade simulation and performance tracking.
📌 This is a strategy script — It simulates real trades using strategy.entry() and strategy.exit() with full money management for risk-based backtesting.
🧠 Core Logic & Trade Conditions
🔹 BUY Signal Trigger:
At 09:00 a.m. NY (New York time), if:
The current candle is bullish (close > open)
→ A BUY order is placed at the candle’s close price (EP)
Only one signal is evaluated per day.
⚙️ Stop Loss / Take Profit Logic
SL can be:
Wick low (0%)
Or dynamically calculated using a % of the full candle range
TP is calculated using the user-defined Risk/Reward ratio (e.g., 1:4)
The TP and SL levels are passed to strategy.exit() for each trade simulation.
💰 Risk Management & Lot Size Calculation
Before placing the trade:
The system calculates pip distance from EP to SL
Computes the lot size based on:
Account capital
Risk % per trade
Pip value (auto or manual)
This ensures every trade uses consistent, scalable risk regardless of instrument.
🕒 Manual Close at 3:00 p.m. NY
If the trade is still open by 15:00 NY time, it will be closed using strategy.close().
The final result is the actual % gain/loss based on how far price moved relative to SL.
📊 Backtest Accuracy
One trade per day
LIMIT order at the candle close
SL and TP pre-defined at execution
No repainting
Session-restricted (only runs on 1H timeframe)
✅ Ideal For:
Traders who want to backtest a clean and simple daily entry system
Strategy developers seeking reproducible, high-conviction trades
Users who prefer non-repainting, session-based simulations
👨💻 Credits:
💡 Developed by: LANZ
🧠 Logic & Money Management Engine: LANZ
📈 Designed for: 1H charts
🧪 Purpose: Accurate simulation of LANZ 6.0's NY Candle Entry system
Strategy Chameleon [theUltimator5]Have you ever looked at an indicator and wondered to yourself "Is this indicator actually profitable?" Well now you can test it out for yourself with the Strategy Chameleon!
Strategy Chameleon is a versatile, signal-agnostic trading strategy designed to adapt to any external indicator or trading system. Like a chameleon changes colors to match its environment, this strategy adapts to match any buy/sell signals you provide, making it the ultimate backtesting and automation tool for traders who want to test multiple strategies without rewriting code.
🎯 Key Features
1) Connects ANY external indicator's buy/sell signals
Works with RSI, MACD, moving averages, custom indicators, or any Pine Script output
Simply connect your indicator's signal output to the strategy inputs
2) Multiple Stop Loss Types:
Percentage-based stops
ATR (Average True Range) dynamic stops
Fixed point stops
3) Advanced Trailing Stop System:
Percentage trailing
ATR-based trailing
Fixed point trailing
4) Flexible Take Profit Options:
Risk:Reward ratio targeting
Percentage-based profits
ATR-based profits
Fixed point profits
5) Trading Direction Control
Long Only - Bull market strategies
Short Only - Bear market strategies
Both - Full market strategies
6) Time-Based Filtering
Optional trading session restrictions
Customize active trading hours
Perfect for day trading strategies
📈 How It Works
Signal Detection: The strategy monitors your connected buy/sell signals
Entry Logic: Executes trades when signals trigger during valid time periods
Risk Management: Automatically applies your chosen stop loss and take profit levels
Trailing System: Dynamically adjusts stops to lock in profits
Performance Tracking: Real-time statistics table showing win rate and performance
⚙️ Setup Instructions
0) Add indicator you want to test, then add the Strategy to your chart
Connect Your Signals:
imgur.com
Go to strategy settings → Signal Sources
1) Set "Buy Signal Source" to your indicator's buy output
2) Set "Sell Signal Source" to your indicator's sell output
3) Choose table position - This simply changes the table location on the screen
4) Set trading direction preference - Buy only? Sell only? Both directions?
imgur.com
5) Set your preferred stop loss type and level
You can set the stop loss to be either percentage based or ATR and fully configurable.
6) Enable trailing stops if desired
imgur.com
7) Configure take profit settings
8) Toggle time filter to only consider specific time windows or trading sessions.
🚀 Use Cases
Test various indicators to determine feasibility and/or profitability.
Compare different signal sources quickly
Validate trading ideas with consistent risk management
Portfolio Management
Apply uniform risk management across different strategies
Standardize stop loss and take profit rules
Monitor performance consistently
Automation Ready
Built-in alert conditions for automated trading
Compatible with trading bots and webhooks
Easy integration with external systems
⚠️ Important Notes
This strategy requires external signals to function
Default settings use 10% of equity per trade
Pyramiding is disabled (one position at a time)
Strategy calculates on bar close, not every tick
🔗 Integration Examples
Works perfectly with:
RSI strategies (connect RSI > 70 for sells, RSI < 30 for buys)
Moving average crossovers
MACD signal line crosses
Bollinger Band strategies
Custom oscillators and indicators
Multi-timeframe strategies
📋 Default Settings
Position Size: 10% of equity
Stop Loss: 2% percentage-based
Trailing Stop: 1.5% percentage-based (enabled)
Take Profit: Disabled (optional)
Trade Direction: Both long and short
Time Filter: Disabled
MACD Liquidity Tracker Strategy [Quant Trading]MACD Liquidity Tracker Strategy
Overview
The MACD Liquidity Tracker Strategy is an enhanced trading system that transforms the traditional MACD indicator into a comprehensive momentum-based strategy with advanced visual signals and risk management. This strategy builds upon the original MACD Liquidity Tracker System indicator by TheNeWSystemLqtyTrckr , converting it into a fully automated trading strategy with improved parameters and additional features.
What Makes This Strategy Original
This strategy significantly enhances the basic MACD approach by introducing:
Four distinct system types for different market conditions and trading styles
Advanced color-coded histogram visualization with four dynamic colors showing momentum strength and direction
Integrated trend filtering using 9 different moving average types
Comprehensive risk management with customizable stop-loss and take-profit levels
Multiple alert systems for entry signals, exits, and trend conditions
Flexible signal display options with customizable entry markers
How It Works
Core MACD Calculation
The strategy uses a fully customizable MACD configuration with traditional default parameters:
Fast MA : 12 periods (customizable, minimum 1, no maximum limit)
Slow MA : 26 periods (customizable, minimum 1, no maximum limit)
Signal Line : 9 periods (customizable, now properly implemented and used)
Cryptocurrency Optimization : The strategy's flexible parameter system allows for significant optimization across different crypto assets. Traditional MACD settings (12/26/9) often generate excessive noise and false signals in volatile crypto markets. By using slower, more smoothed parameters, traders can capture meaningful momentum shifts while filtering out market noise.
Example - DOGE Optimization (45/80/290 settings) :
• Performance : Optimized parameters yielding exceptional backtesting results with 29,800% PnL
• Why it works : DOGE's high volatility and social sentiment-driven price action benefits from heavily smoothed indicators
• Timeframes : Particularly effective on 30-minute and 4-hour charts for swing trading
• Logic : The very slow parameters filter out noise and capture only the most significant trend changes
Other Optimizable Cryptocurrencies : This parameter flexibility makes the strategy highly effective for major altcoins including SUI, SEI, LINK, Solana (SOL) , and many others. Each crypto asset can benefit from custom parameter tuning based on its unique volatility profile and trading characteristics.
Four Trading System Types
1. Normal System (Default)
Long signals : When MACD line is above the signal line
Short signals : When MACD line is below the signal line
Best for : Swing trading and capturing longer-term trends in stable markets
Logic : Traditional MACD crossover approach using the signal line
2. Fast System
Long signals : Bright Blue OR Dark Magenta (transparent) histogram colors
Short signals : Dark Blue (transparent) OR Bright Magenta histogram colors
Best for : Scalping and high-volatility markets (crypto, forex)
Logic : Leverages early momentum shifts based on histogram color changes
3. Safe System
Long signals : Only Bright Blue histogram color (strongest bullish momentum)
Short signals : All other colors (Dark Blue, Bright Magenta, Dark Magenta)
Best for : Risk-averse traders and choppy markets
Logic : Prioritizes only the strongest bullish signals while treating everything else as bearish
4. Crossover System
Long signals : MACD line crosses above signal line
Short signals : MACD line crosses below signal line
Best for : Precise timing entries with traditional MACD methodology
Logic : Pure crossover signals for more precise entry timing
Color-Coded Histogram Logic
The strategy uses four distinct colors to visualize momentum:
🔹 Bright Blue : MACD > 0 and rising (strong bullish momentum)
🔹 Dark Blue (Transparent) : MACD > 0 but falling (weakening bullish momentum)
🔹 Bright Magenta : MACD < 0 and falling (strong bearish momentum)
🔹 Dark Magenta (Transparent) : MACD < 0 but rising (weakening bearish momentum)
Trend Filter Integration
The strategy includes an advanced trend filter using 9 different moving average types:
SMA (Simple Moving Average)
EMA (Exponential Moving Average) - Default
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
LSMA (Least Squares Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
VIDYA (Variable Index Dynamic Average)
Default Settings : 50-period EMA for trend identification
Visual Signal System
Entry Markers : Blue triangles (▲) below candles for long entries, Magenta triangles (▼) above candles for short entries
Candle Coloring : Price candles change color based on active signals (Blue = Long, Magenta = Short)
Signal Text : Optional "Long" or "Short" text inside entry triangles (toggleable)
Trend MA : Gray line plotted on main chart for trend reference
Parameter Optimization Examples
DOGE Trading Success (Optimized Parameters) :
Using 45/80/290 MACD settings with 50-period EMA trend filter has shown exceptional results on DOGE:
Performance : Backtesting results showing 29,800% PnL demonstrate the power of proper parameter optimization
Reasoning : DOGE's meme-driven volatility and social sentiment spikes create significant noise with traditional MACD settings
Solution : Very slow parameters (45/80/290) filter out social media-driven price spikes while capturing only major momentum shifts
Optimal Timeframes : 30-minute and 4-hour charts for swing trading opportunities
Result : Exceptionally clean signals with minimal false entries during DOGE's characteristic pump-and-dump cycles
Multi-Crypto Adaptability :
The same optimization principles apply to other major cryptocurrencies:
SUI : Benefits from smoothed parameters due to newer coin volatility patterns
SEI : Requires adjustment for its unique DeFi-related price movements
LINK : Oracle news events create price spikes that benefit from noise filtering
Solana (SOL) : Network congestion events and ecosystem developments need smoothed detection
General Rule : Higher volatility coins typically benefit from very slow MACD parameters (40-50 / 70-90 / 250-300 ranges)
Key Input Parameters
System Type : Choose between Fast, Normal, Safe, or Crossover (Default: Normal)
MACD Fast MA : 12 periods default (no maximum limit, consider 40-50 for crypto optimization)
MACD Slow MA : 26 periods default (no maximum limit, consider 70-90 for crypto optimization)
MACD Signal MA : 9 periods default (now properly utilized, consider 250-300 for crypto optimization)
Trend MA Type : EMA default (9 options available)
Trend MA Length : 50 periods default (no maximum limit)
Signal Display : Both, Long Only, Short Only, or None
Show Signal Text : True/False toggle for entry marker text
Trading Applications
Recommended Use Cases
Momentum Trading : Capitalize on strong directional moves using the color-coded system
Trend Following : Combine MACD signals with trend MA filter for higher probability trades
Scalping : Use "Fast" system type for quick entries in volatile markets
Swing Trading : Use "Normal" or "Safe" system types for longer-term positions
Cryptocurrency Trading : Optimize parameters for individual crypto assets (e.g., 45/80/290 for DOGE, custom settings for SUI, SEI, LINK, SOL)
Market Suitability
Volatile Markets : Forex, crypto, indices (recommend "Fast" system or smoothed parameters)
Stable Markets : Stocks, ETFs (recommend "Normal" or "Safe" system)
All Timeframes : Effective from 1-minute charts to daily charts
Crypto Optimization : Each major cryptocurrency (DOGE, SUI, SEI, LINK, SOL, etc.) can benefit from custom parameter tuning. Consider slower MACD parameters for noise reduction in volatile crypto markets
Alert System
The strategy provides comprehensive alerts for:
Entry Signals : Long and short entry triangle appearances
Exit Signals : Position exit notifications
Color Changes : Individual histogram color alerts
Trend Conditions : Price above/below trend MA alerts
Strategy Parameters
Default Settings
Initial Capital : $1,000
Position Size : 100% of equity
Commission : 0.1%
Slippage : 3 points
Date Range : January 1, 2018 to December 31, 2069
Risk Management (Optional)
Stop Loss : Disabled by default (customizable percentage-based)
Take Profit : Disabled by default (customizable percentage-based)
Short Trades : Disabled by default (can be enabled)
Important Notes and Limitations
Backtesting Considerations
Uses realistic commission (0.1%) and slippage (3 points)
Default position sizing uses 100% equity - adjust based on risk tolerance
Stop-loss and take-profit are disabled by default to show raw strategy performance
Strategy does not use lookahead bias or future data
Risk Warnings
Past performance does not guarantee future results
MACD-based strategies may produce false signals in ranging markets
Consider combining with additional confluences like support/resistance levels
Test thoroughly on demo accounts before live trading
Adjust position sizing based on your risk management requirements
Technical Limitations
Strategy does not work on non-standard chart types (Heikin Ashi, Renko, etc.)
Signals are based on close prices and may not reflect intraday price action
Multiple rapid signals in volatile conditions may result in overtrading
Credits and Attribution
This strategy is based on the original "MACD Liquidity Tracker System" indicator created by TheNeWSystemLqtyTrckr . This strategy version includes significant enhancements:
Complete strategy implementation with entry/exit logic
Addition of the "Crossover" system type
Proper implementation and utilization of the MACD signal line
Enhanced risk management features
Improved parameter flexibility with no artificial maximum limits
Additional alert systems for comprehensive trade management
The original indicator's core color logic and visual system have been preserved while expanding functionality for automated trading applications.
DOGE 15MIN**Warm Reminder:** This strategy is intended solely for exploratory research and experimentation to evaluate the effectiveness of various signals. Drawing inspiration from patterns observed on the DOGE cryptocurrency 15-minute chart, it provides a tailored framework to identify potential trading opportunities. For optimal results, it is currently recommended exclusively for DOGE 15min charts. Remember, trading involves inherent risks, and past performance is not indicative of future results. We are dedicated to ongoing optimizations and refinements to enhance its robustness across broader applications—stay tuned for updates!
#### **A. Long Entry Signals**
These conditions trigger a long position entry, provided the strategy has no existing position (position_size == 0) and is not blocked. Signals can be enabled/disabled via input toggles (e.g., enable_vix).
- **VIX Reversal (vix_long)**: VIX signal shifts from high to low volatility (non-high volatility), with RSI between 30-50.
- **RSI Oversold (rsi_long)**: RSI crosses above 30.
- **CVD Bullish (cvd_long)**: CVD is rising.
- **Price RSI Bullish (prsi_long)**: Price RSI crosses above 30 or a long signal is triggered.
- **RangeEMA Bullish (rema_long)**: Candlestick is above POC, with KAMA trend flipping upward.
- **ZVWAP Oversold (zvwap_long)**: ZVWAP enters the oversold zone.
- **KAMA + Volume Bullish (kama_long)**: KAMA trend flips upward, candlestick is above POC, volume is rising, and the candle is bullish (green).
- **Volume Burst Bullish (vol_burst_long)**: Volume RSI crosses below threshold (default 70), open > close (bearish/red candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_long, Pivot, OI, RSI/ADX extreme filters).
#### **B. Short Entry Signals**
Similar to long entries: requires no existing position and no blocks.
- **RSI Overbought (rsi_short)**: RSI crosses below 70.
- **CVD Bearish (cvd_short)**: CVD is declining.
- **Price RSI Bearish (prsi_short)**: Price RSI crosses below 70 or a short signal is triggered.
- **RangeEMA Bearish (rema_short)**: Candlestick is below POC, with KAMA trend flipping downward.
- **ZVWAP Overbought (zvwap_short)**: ZVWAP enters the overbought zone.
- **KAMA + Volume Bearish (kama_short)**: KAMA trend flips downward, candlestick is below POC, volume is declining, and the candle is bearish (red).
- **Chop Bearish (chop_short)**: Chop crosses below 38.2, with RSI > 50.
- **Volume Burst Bearish (vol_burst_short)**: Volume RSI crosses below threshold (default 70), RSI > 70, and close > open (bullish/green candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_short, Pivot, OI, RSI/ADX extreme filters).
#### **C. Long Entry Blocks/Filters**
These conditions block long entries unless the signal ignores blocks (e.g., Volume Burst).
- **Base Prohibition (not_long)**: Volume is declining, or ADX is bearish (di_bear), or VIX is in high volatility (vix_flag), or RSI < 30.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is declining.
- **RSI/ADX Extreme Filter**: RSI > 70 or ADX is bullish (di_bull).
- **Other**: Strategy already has a position (position_size != 0), or extreme volatility (is_extreme, though disabled in code).
#### **D. Short Entry Blocks/Filters**
Similar to long blocks.
- **Base Prohibition (not_short)**: Volume is rising, or (Chop < 38.2 and RSI > 50), or ADX is bullish (di_bull), or RSI > 70.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is rising.
- **RSI/ADX Extreme Filter**: RSI < 30 or ADX is bearish (di_bear).
- **Other**: Existing position, or extreme volatility.
#### **E. Long Exit Signals**
Triggers closing of long positions, based on states (e.g., super_long, weak_long, only_kama).
- **KAMA Bearish Flip (exist_long)**: KAMA trend flips downward, or KAMA is downward with a short signal.
- **VIX Signal**: VIX shifts from low to high volatility, with RSI < 50.
- **Reversal Signal**: Short signal present and KAMA is downward.
- **Weak Trend Stop-Loss (weak_stop_long)**: In weak_long state, candlestick near POC, and close crosses below POC.
- **Weak KAMA Stop-Loss (weak_kama_long)**: In weak_long state, candlestick far from POC, and KAMA trend reverses.
- **Global Exit (exist_all)**: Volume RSI crosses below threshold (vol_under), or KAMA exit (kama_exit_long), or weak stop-loss, etc.
- **Special**: If in strong_long_hold (only_kama and KAMA remains bullish), ignore certain exit signals to hold the position.
#### **F. Short Exit Signals**
Similar to long exits.
- **KAMA Bullish Flip (exist_short)**: KAMA trend flips upward, or KAMA is upward with a long signal.
- **Reversal Signal**: Long signal present and KAMA is upward.
- **Weak Trend Stop-Loss (weak_stop_short)**: In weak_short state, candlestick near POC, and close crosses above short_state.current_max.
- **Weak KAMA Stop-Loss (weak_kama_short)**: In weak_short state, candlestick far from POC, and KAMA flips upward.
- **Global Exit (exist_all)**: Same as above.
EMA and Dow Theory Strategies🌐 Strategy Description
📘 Overview
This is a hybrid strategy that combines EMA crossovers, Dow Theory swing logic, and multi-timeframe trend overlays. It is suitable for intraday to short-term trading on any asset class: crypto, forex, stocks, and indices.
The strategy provides precise entry/exit signals, dynamic stop-loss and scale-out, and highly visual trade guidance.
🧠 Key Features
・Dual EMA crossover system (applied to both symbol and external index)
・Dow Theory-based swing high/low detection for trend confirmation
・Visual overlay of higher timeframe swing trend (htfTrend)
・RSI filter to avoid overbought/oversold entries
・Dynamic partial take-profit when trend weakens
・Custom stop-loss (%) control
・Visualized trade PnL labels directly on chart
・Alerts for entry, stop-loss, partial exit
・Gradient background zones for swing zones and trend visualization
・Auto-tracked metrics: APR, drawdown, win rate, equity curve
⚙️ Input Parameters
| Parameter | Description |
| ------------------------- | -------------------------------------------------------- |
| Fast EMA / Slow EMA | Periods for detecting local trend via EMAs |
| Index Fast EMA / Slow EMA | EMAs applied to external reference index |
| StopLoss | Maximum loss threshold in % |
| ScaleOut Threshold | Scale-out percentage when trend changes color |
| RSI Period / Levels | RSI period and overbought/oversold levels |
| Swing Detection Length | Number of bars used to detect swing highs/lows |
| Stats Display Options | Toggle PnL labels and position of statistics table |
🧭 About htfTrend (Higher Timeframe Trend)
The script includes a higher timeframe trend (htfTrend) calculated using Dow Theory (pivot highs/lows).
This trend is only used for visual guidance, not for actual entry conditions.
Why? Strictly filtering trades by higher timeframe often leads to missed opportunities and low frequency.
By keeping htfTrend visual-only, traders can still refer to macro structure but retain trade flexibility.
Use it as a contextual tool, not a constraint.
ストラテジー説明
📘 概要
本ストラテジーは、EMAクロスオーバー、ダウ理論によるスイング判定、**上位足トレンドの視覚表示（htfTrend）**を組み合わせた複合型の短期トレーディング戦略です。
仮想通貨・FX・株式・指数など幅広いアセットに対応し、デイトレード〜スキャルピング用途に適しています。
動的な利確/損切り、視覚的にわかりやすいエントリー/イグジット、統計表示を搭載しています。
🧠 主な機能
・対象銘柄＋外部インデックスのEMAクロスによるトレンド判定
・ダウ理論に基づいたスイング高値・安値検出とトレンド判断
・上位足スイングトレンド（htfTrend）の視覚表示
・RSIフィルターによる過熱・売られすぎの回避
・トレンドの弱まりに応じた部分利確（スケールアウト）
・**損切り閾値（％）**をカスタマイズ可能
・チャート上に損益ラベル表示
・アラート完備（エントリー・決済・部分利確）
・トレンドゾーンを可視化する背景グラデーション
・勝率・ドローダウン・APR・資産増加率などの自動表示
| 設定項目名 | 説明内容 |
| --------------------- | -------------------------- |
| Fast EMA / Slow EMA | 銘柄に対して使用するEMAの期間設定 |
| Index Fast / Slow EMA | 外部インデックスのEMA設定 |
| 損切り（StopLoss） | 損切りラインのしきい値（%で指定） |
| 部分利確しきい値 | トレンド弱化時にスケールアウトする割合（%） |
| RSI期間・水準 | RSI計算期間と、過熱・売られすぎレベル設定 |
| スイング検出期間 | スイング高値・安値の検出に使用するバー数 |
| 統計表示の切り替え | 損益ラベルや統計テーブルの表示／非表示選択 |
🧭 上位足トレンド（htfTrend）について
本スクリプトには、上位足でのスイング高値・安値の更新に基づく**htfTrend（トレンド判定）が含まれています。
これは視覚的な参考情報であり、エントリーやイグジットには直接使用されていません。**
その理由は、上位足を厳密にロジックに組み込むと、トレード機会の損失が増えるためです。
このスクリプトでは、**判断の補助材料として「表示のみに留める」**設計を採用しています。
→ 裁量で「利確を早める」「逆張りを避ける」判断に活用可能です。
Eliora Gold 1min (Heikin Ashi)Eliora -focused trading strategy designed for anything on the 1-minute timeframe using Heikin Ashi candles. This mode combines advanced market logic with structured risk management to deliver smooth, disciplined trade execution.
Key Features:
✅ Trend Confirmation – Aligns with dominant market direction for higher accuracy.
✅ ATR-Based Volatility Filter – Avoids high-risk conditions and chaotic price action.
✅ Candle Strength Logic – Filters weak setups, focusing on strong momentum.
✅ Balanced Risk/Reward – Calculates stop-loss and take-profit dynamically for consistent results.
✅ Cooldown & Overtrade Protection – Limits frequency to maintain trade quality.
This version of Eliora is built for scalpers and intraday traders seeking high-probability entries with graceful exits.
Auto Intelligence Selective Moving Average(AI/MA)# 🤖 Auto Intelligence Moving Average Strategy (AI/MA)
**AI/MA** is a state-adaptive moving average crossover strategy designed to **maximize returns from golden cross / death cross logic** by intelligently switching between different MA types and parameters based on market conditions.
---
## 🎯 Objective
To build a moving average crossover strategy that:
- **Adapts dynamically** to market regimes (trend vs range, rising vs falling)
- **Switches intelligently** between SMA, EMA, RMA, and HMA
- **Maximizes cumulative return** under realistic backtesting
---
## 🧪 materials amd methods
- **MA Types Considered**: SMA, EMA, RMA, HMA
- **Parameter Ranges**: Periods from 5 to 40
- **Market Conditions Classification**:
- Based on the slope of a central SMA(20) line
- And the relative position of price to the central line
- Resulting in 4 regimes: A (Bull), B (Pullback), C (Rebound), D (Bear)
- **Optimization Dataset**:
- **Bybit BTCUSDT.P**
- **1-hour candles**
- **2024 full-year**
- **Search Process**:
- **Random search**: 200 parameter combinations
- Evaluated by:
- `Cumulative PnL`
- `Sharpe Ratio`
- `Max Drawdown`
- `R² of linear regression on cumulative PnL`
- **Implementation**:
- Optimization performed in **Python (Pandas + Matplotlib + Optuna-like logic)**
- Final parameters ported to **Pine Script (v5)** for TradingView backtesting
---
## 📈 Performance Highlights (on optimization set)
| Timeframe | Return (%) | Notes |
|-----------|------------|----------------------------|
| 6H | +1731% | Strongest performance |
| 1D | +1691% | Excellent trend capture |
| 12H | +1438% | Balance of trend/range |
| 5min | +27.3% | Even survives scalping |
| 1min | +9.34% | Robust against noise |
- Leverage: 100x
- Position size: 100%
- Fees: 0.055%
- Margin calls: **none** 🎯
---
## 🛠 Technology Stack
- `Python` for data handling and optimization
- `Pine Script v5` for implementation and visualization
- Fully state-aware strategy, modular and extendable
---
## ✨ Final Words
This strategy is **not curve-fitted**, **not over-parameterized**, and has been validated across multiple timeframes. If you're a fan of dynamic, intelligent technical systems, feel free to use and expand it.
💡 The future of simple-yet-smart trading begins here.
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).
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#### **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.
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#### **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.
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#### **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.
