指標和策略
4H Confirmation + 1H SFP BOS Retest4H Confirmation + 1H Entry (SFP + BOS + Retest)Run it on 1H
Uses 4H EMAs for higher-timeframe direction (confirmation)
Uses 1H SFP + BOS + retest + RSI for entries
This gives you more trades, still guided by the 4H trend
stormytrading orb botshows entries for 15m orb based on 5m break and retest made solely for mnq or nq, works good with smt
shows trades for ldn, nyc, nyc overlap and Asia session, pls follow stormy trading on insta for more
HMA+RVOL Strategy Hariss 369The Hull Moving Average (HMA) is a smooth, fast, and highly responsive moving average created by Alan Hull. It reduces lag significantly while still maintaining smoothness, making it one of the most popular tools for trend detection and entries. It is widely used for trend filter. Hull Moving Average(HMA) with RVOL strengthens the trend as volume is prime factor of price movement.
Trading with HMA: Simple method is buy when price closes above HMA , stop less below the low of last candle and target is 1.5 or 2 times of stop loss. The reverse is for sell. The HMA automatically turns to green on bull trend and red on bear trend for better visual confirmation.
Adding RVOL to HMA is better method of trading. Buy signal is initiated when price closes above HMA and RVOL is greater than 1.2. Sell signal is initiated when price closes below 89 HMA and rovl is greater than 1.2. One can change the value of RVOL according to trading style and type asset being traded.
It is a back tested strategy.
yangwen1.0This script is an initial concept of mine. I attempted to use the 5-minute chart as ticks for catching bottoms and picking tops, but it's unable to avoid whipsaws. I've tested many methods to evade whipsaws, but they ultimately result in poor entry points, causing me to miss the bottoms and tops of price swings. I sincerely hope someone with better approaches can discuss this with me. Thank you.
DEMA ATR Strategy [PrimeAutomation]⯁ OVERVIEW
The DEMA ATR Strategy combines trend-following logic with adaptive volatility filters to identify strong momentum phases and manage trades dynamically.
It uses a Double Exponential Moving Average (DEMA) anchored to ATR volatility bands, creating a self-adjusting trend baseline.
When the adjusted DEMA shifts direction, the strategy enters positions and scales out profit in phases based on ATR-driven targets.
This system adapts to volatility, filters noise, and seeks sustained directional moves.
⯁ KEY FEATURES
DEMA-Volatility Hybrid Filter
Uses Double EMA with ATR expansion/compression logic to form a dynamic trend baseline.
Directional Shift Entries
Entries occur when the adjusted DEMA flips trend (bullish crossover or bearish crossunder vs its past value).
Noise Reduction Mechanism
ATR range caps extreme moves and prevents false flips during choppy volatility spikes.
Multi-Level Take Profits
Targets scale out positions at 1×, 2×, and 3× ATR multiples in the trade direction.
Volatility-Adaptive Targets
ATR multiplier ensures profit targets expand/contract based on market conditions.
Single-Direction Exposure
No pyramiding; the strategy flips position only when trend shifts.
Automated Trade Finalization
When all profit targets trigger, the position is fully closed.
⯁ STRATEGY LOGIC
Trend Direction:
DEMA baseline is modified using ATR upper/lower envelopes.
• If the adjusted DEMA rises above previous value → Bullish
• If it falls below previous value → Bearish
Entry Rules:
• Enter Long when bullish shift occurs and no long position exists
• Enter Short when bearish shift occurs and no short position exists
Take Profit Logic:
3 partial exits for each trade based on ATR:
• TP1 = ±1× ATR
• TP2 = ±2× ATR
• TP3 = ±3× ATR
Profit distribution: 30% / 30% / 40%
Exit Conditions:
• Exit when all TPs hit (full scale-out if sum of all TPs 100%)
• Opposite trend signal closes current trade and opens new one
⯁ WHEN TO USE
Trending environments
Medium–high volatility phases
Swing trading and intraday trend plays
Markets that respect momentum continuation (crypto, indices, FX majors)
⯁ CONCLUSION
This strategy blends DEMA trend recognition with ATR-based volatility adaptation to generate cleaner directional entries and structured take-profit exits. It is designed to capture momentum phases while avoiding noise-driven false signals, delivering a disciplined and scalable trend-following approach.
BTC 30 m Long singal Asset: Bitcoin only
Timeframe: 30 minutes
Entry Conditions (Long):
MACD histogram turns from red to green (negative to positive)
Stochastic K line crosses above D line AND this crossover happens below the lower band (20)
RSI is above the middle band (50)
ai cruhsera pullback strategy to donchain lower and upperbands.. best for cypro lower timeframe scalping..
Crypto Edition 0.2This strategy is built on a trend-following approach, designed to capture sustained market momentum rather than predict reversals.its a pullback strategy. The goal is to stay aligned with the prevailing trend, ride strong moves, avoid ranging-market noiseE
Alt Trading: FuturesOne
The FuturesOne Indicator + Strategy will be continuously enhanced to ensure our users receive the most effective and profit-focused trading system at the best possible value. Version 0 (V0) of the FuturesOne Strategy is built on a refined Opening Range Breakout (ORB) framework, augmented with a quantitative regime-detection and filtering layer. This design allows users to tailor their approach: they may opt for consistent daily ORB opportunities or select a mode that applies quantitative filters to surface fewer, but higher-probability, trade setups.
Crypto Grid 2025+ Long Only (Asym TP)Crypto Grid 2025+ Long Only (Asymmetric Take-Profit) is a long-only mean-reversion grid strategy designed for intraday cryptocurrency trading.
The core idea is to accumulate long positions as price moves downward within a locally defined price range and to exit positions on upward retracements.
The strategy automatically builds a multi-level grid between the highest and lowest price over a user-defined lookback period (“range length”). Each grid level acts as a potential entry point when price crosses it from above.
Key Features
1. Long-only grid logic
The strategy opens long positions only, progressively increasing exposure as price moves into lower grid levels.
2. Asymmetric take-profit mechanism
Instead of taking profit strictly at the next grid level, the strategy allows targeting multiple levels above the entry point. This increases the average profit per winning trade and shifts the reward-to-risk profile toward larger, less frequent wins.
3. Optional partial take-profit
A portion of each trade can be closed at the nearest grid level, while the remainder is held for a more distant asymmetric target. This balances consistency and profit potential.
4. Volume-based market filter
Entries can be restricted to periods of healthy market activity by requiring volume to exceed a moving-average baseline.
5. Capital-scaled position sizing
Position size is determined by risk percentage, grid spacing, and a dynamic sizing mode (original / conservative / aggressive).
6. Built-in risk controls
global stop below the lower boundary of the range,
global take-profit above the upper boundary,
automatic shutdown after a configurable loss-streak.
Market Philosophy
This strategy belongs to the mean-reversion family: it expects short-term overshoots to revert back toward mid-range liquidity zones.
It is not trend-following.
It performs best in choppy, range-bound, or slow-grinding markets — especially on liquid crypto pairs.
Recommended Use Cases
Short timeframes (1–15 minutes)
High-liquidity crypto pairs
Sideways or rotational price action
Exchanges with low fees (due to higher order count)
Not Intended For
Strong trending markets without pullbacks
Assets with thin order books
Use with leverage without additional risk controls
Summary
Crypto Grid 2025+ Long Only (Asymmetric TP) is a refined grid-based mean-reversion strategy optimized for modern crypto markets. Its asymmetric take-profit framework is specifically engineered to reduce the classical issue of “small wins and large occasional losses” found in traditional grid systems, giving it a more favorable long-term trade distribution.
AkdakTrading1Script using M5 Order Blocks with an FVG and the first blocks of an impulse to take trades with a 1:1 risk-reward.
ZanScritp 1:3 | 21.00-22.00 WIB | XAUUSD TF 5MStrategy Overview (Short & Simple Explanation)
This strategy focuses on taking high-quality trades during a specific hour of the day (20:00–21:00 WIB), when market movement is often more reliable. It looks for clear trends, avoids extreme market conditions, and only trades when volatility is healthy.
It uses a fixed Risk–Reward of 1:2, meaning every trade aims for twice the potential profit compared to the risk. Stop Loss (SL) and Take Profit (TP) levels are set immediately when a trade opens and never move afterward.
When a buy or sell signal appears, the strategy automatically draws:
An entry line
A Stop Loss line
A Take Profit line
A label showing the trade information
The system is designed to avoid “repainting,” ensuring trade entries stay consistent, while SL and TP always trigger exactly when price touches them—creating a stable and predictable trading workflow.
Target Audience
This strategy is designed for:
1. Beginner to Intermediate Traders
Those who want a simple, rule-based system focused on:
Clear trend direction
Fixed risk-reward
Easy-to-understand SL/TP logic
2. Scalpers & Intraday Traders
Traders who prefer:
Short trading windows
High-probability session filtering
Clean execution without repainting
Oracle Protocol — Arch Public (Testing Clone) Oracle Protocol — Arch Public Series (testing clone)
This model implements the Arch Public Oracle structure: a systematic accumulation-and-distribution engine built around a dynamic Accumulation Cost Base (ACB), strict profit-gate exit logic, and a capital-bounded flywheel reinvestment system.
It is designed for transparent execution, deterministic behaviour, and rule-based position management.
Core Function Set
1. Accumulation Framework (ACB-Driven)
The accumulation engine evaluates market movement against defined entry conditions, including:
Percentage-based entry-drop triggers
Optional buy-below-ACB mode
Capital-gated entries tied to available ledger balance
Fixed-dollar and min-dollar entry rules (as seen in Arch public materials)
Automated sizing through flywheel capital
Range-bounded ledger for controlled backtesting input
Each qualifying buy updates the live ACB, maintains the internal ledger, and forms the next reference point for exit evaluation.
No forecasting mechanisms are included.
2. Profit-Gate Exit System
Exits are governed by the standard Arch public approach:
A sealed ACB reference for threshold evaluation
Optional live-ACB visibility
Profit-gate triggers defined per asset class
Candle-confirmation integration (“ProfitGate + Candle” mode)
Distribution only when the smallest active threshold is met
This provides a consistent cadence with published Arch diagrams and PDFs.
3. Once-Per-Rally Governance
After a distribution, the algorithm locks until price retraces below the most recent accumulation base.
Only after re-arming can the next profit gate activate.
This prevents over-frequency selling and aligns with the public-domain Oracle behaviour.
4. Quiet-Bars & Threshold Cluster Control
A volatility-stabilisation layer prevents multiple exits from micro-fluctuations or transient spikes.
This ensures clean execution during fast markets and high volatility.
5. Flywheel Reinvestment
Distribution proceeds automatically return to the capital pool where permitted, creating a closed system of:
Entry sizing
Exit proceeds
Ledger-managed capital state
All sizing respects capital boundaries and does not breach dollar floors or overrides.
6. Automation Hooks and Integration
The script exposes:
3Commas-compatible JSON sizing
Entry/exit signalling via alertcondition()
Deterministic event reporting suitable for external automation
This allows consistent deployment across automated execution environments.
7. Visual Tooling
Optional displays include:
Live ACB line
Exit-guide markers
Capital, state, and ledger panels
Realized/unrealized outcome tracking based on internal logic only
Visual components do not influence execution rules.
Operating Notes
This model is rule-based, deterministic, and non-predictive.
It executes only according to the explicit thresholds, capital limits, and state transitions defined within the script.
No discretionary or forward-looking logic is included.
CSS_LFU_v0.1Overview:
A multi-factor, market-adaptive swing strategy designed for intraday and short-term crypto trading. It synthesizes momentum, volatility, and trend signals into a unified composite score over a configurable lookback window. The strategy leverages a modular, signal-weighted approach to ensure robust entry timing while remaining compatible with human-in-the-loop validation and algorithmic execution.
Core Modules:
AJFFRSI (RSX-based Momentum): Measures smoothed price momentum with noise-reduction filters to detect crossovers relative to the QQE trailing stop.
QQE (Quantitative Qualitative Easing RSI): A modified RSI with a dynamic trailing stop that adapts to short-term volatility, identifying exhaustion and potential reversal points.
Keltner Channel Zones: Determines overextension relative to trend, providing buy/sell zones based on ATR-banded EMA.
WaveTrend Oscillator: Confirms short-term swings and market direction through smoothed oscillator cross signals.
Rolling Composite Score: Aggregates module signals over a unified lookback (e.g., 144 bars) to normalize noise and capture consistent trends.
Signal Logic:
Each module outputs a discrete score (+1 / 0 / -1).
The rolling composite score sums all module scores over the lookback period.
Long positions trigger when the rolling score meets or exceeds the long threshold.
Short positions trigger when the rolling score meets or falls below the short threshold.
Multi-dimensional signal aggregation reduces false positives from single indicators.
Rolling lookback ensures score normalization across different volatility regimes.
Highly modular: easy to adapt modules or weights to different instruments or timeframes.
Fully compatible with automated execution pipelines, including custom exchange screener bots.
Use Case:
Ideal for quant-driven altcoin or multi-asset strategies where high-frequency validation is critical and sequential module weighting enhances trend flip detection.
STRATEGY 1 │ Red Dragon │ Model 1 │ Pro │ [Titans_Invest]The Red Dragon Model 1 is a fully automated trading strategy designed to operate BTC/USDT.P on the 4-hour chart with precision, stability, and consistency. It was built to deliver reliable behavior even during strong market movements, maintaining operational discipline and avoiding abrupt variations that could interfere with the trader’s decision-making.
Its core is based on a professionally engineered logical structure that combines trend filters, confirmation criteria, and balanced risk management. Every component was designed to work in an integrated way, eliminating noise, avoiding unnecessary trades, and protecting capital in critical moments. There are no secret mechanisms or hidden logic: everything is built to be objective, clean, and efficient.
Even though it is based on professional quantitative engineering, Red Dragon Model 1 remains extremely simple to operate. All logic is clearly displayed and fully accessible within TradingView itself, making it easy to understand for both beginners and experienced traders. The structure is organized so that any user can quickly view entry conditions, exit criteria, additional filters, adjustable parameters, and the full mechanics behind the strategy’s behavior.
In addition, the architecture was built to minimize unnecessary complexity. Parameters are straightforward, intuitive, and operate in a balanced way without requiring deep adjustments or advanced knowledge. Traders have full freedom to analyze the strategy, understand the logic, and make personal adaptations if desired—always with total transparency inside TradingView.
The strategy was also designed to deliver consistent operational behavior over the long term. Its confirmation criteria reduce impulsive trades; its filters isolate noise; and its overall logic prioritizes high-quality entries in structured market movements. The goal is to provide a stable, clear, and repeatable flow—essential characteristics for any medium-term quantitative approach.
Combining clarity, professional structure, and ease of use, Red Dragon Model 1 offers a solid foundation both for users who want a ready-to-use automated strategy and for those looking to study quantitative models in greater depth.
This entire project was built with extreme dedication, backed by more than 14,000 hours of hands-on experience in Pine Script, continuously refining patterns, techniques, and structures until reaching its current level of maturity. Every line of code reflects this long process of improvement, resulting in a strategy that unites professional engineering, transparency, accessibility, and reliable execution.
🔶 MAIN FEATURES
• Fully automated and robust: Operates without manual intervention, ideal for traders seeking consistency and stability. It delivers reliable performance even in volatile markets thanks to the solid quantitative engineering behind the system.
• Multiple layers of confirmation: Combines 10 key technical indicators with 15 adaptive filters to avoid false signals. It only triggers entries when all trend, market strength, and contextual criteria align.
• Configurable and adaptable filters: Each of the 15 filters can be enabled, disabled, or adjusted by the user, allowing the creation of personalized statistical models for different assets and timeframes. This flexibility gives full freedom to optimize the strategy according to individual preferences.
• Clear and accessible logic: All entry and exit conditions are explicitly shown within the TradingView parameters. The strategy has no hidden components—any user can quickly analyze and understand each part of the system.
• Integrated exclusive tools: Includes complete backtest tables (desktop and mobile versions) with annualized statistics, along with real-time entry conditions displayed directly on the chart. These tools help monitor the strategy across devices and track performance and risk metrics.
• No repaint: All signals are static and do not change after being plotted. This ensures the trader can trust every entry shown without worrying about indicators rewriting past values.
🔷 ENTRY CONDITIONS & RISK MANAGEMENT
Red Dragon Model 1 triggers buy (long) or sell (short) signals only when all configured conditions are satisfied. For example:
• Volume:
• The system only trades when current volume exceeds the volume moving average multiplied by a user-defined factor, indicating meaningful market participation.
• RSI:
• Confirms bullish bias when RSI crosses above its moving average, and bearish bias when crossing below.
• ADX:
• Enters long when +DI is above –DI with ADX above a defined threshold, indicating directional strength to the upside (and the opposite conditions for shorts).
• Other indicators (MACD, SAR, Ichimoku, Support/Resistance, etc.)
Each one must confirm the expected direction before a final signal is allowed.
When all bullish criteria are met simultaneously, the system enters Long; when all criteria indicate a bearish environment, the system enters Short.
In addition, the strategy uses fixed Take Profit and Stop Loss targets for risk control:
Currently: TP around 1.5% and SL around 2.0% per trade, ensuring consistent and transparent risk management on every position.
⚙️ INDICATORS
__________________________________________________________
1) 🔊 Volume: Avoids trading on flat charts.
2) 🍟 MACD: Tracks momentum through moving averages.
3) 🧲 RSI: Indicates overbought or oversold conditions.
4) 🅰️ ADX: Measures trend strength and potential entry points.
5) 🥊 SAR: Identifies changes in price direction.
6) ☁️ Cloud: Accurately detects changes in market trends.
7) 🌡️ R/F: Improves trend visualization and helps avoid pitfalls.
8) 📐 S/R: Fixed support and resistance levels.
9)╭╯MA: Moving Averages.
10) 🔮 LR: Forecasting using Linear Regression.
__________________________________________________________
🟢 ENTRY CONDITIONS 🔴
__________________________________________________________
IF all conditions are 🟢 = 📈 Long
IF all conditions are 🔴 = 📉 Short
__________________________________________________________
🚨 CURRENT TRIGGER SIGNAL 🚨
__________________________________________________________
🔊 Volume
🟢 LONG = (volume) > (MA_volume) * (Volume Mult)
🔴 SHORT = (volume) > (MA_volume) * (Volume Mult)
🧲 RSI
🟢 LONG = (RSI) > (RSI_MA)
🔴 SHORT = (RSI) < (RSI_MA)
🟢 ALL ENTRY CONDITIONS AVAILABLE 🔴
__________________________________________________________
🔊 Volume
🟢 LONG = (volume) > (MA_volume) * (Volume Mult)
🔴 SHORT = (volume) > (MA_volume) * (Volume Mult)
🔊 Volume
🟢 LONG = (volume) > (MA_volume) * (Volume Mult) and (close) > (open)
🔴 SHORT = (volume) > (MA_volume) * (Volume Mult) and (close) < (open)
🍟 MACD
🟢 LONG = (MACD) > (Signal Smoothing)
🔴 SHORT = (MACD) < (Signal Smoothing)
🧲 RSI
🟢 LONG = (RSI) < (Upper)
🔴 SHORT = (RSI) > (Lower)
🧲 RSI
🟢 LONG = (RSI) > (RSI_MA)
🔴 SHORT = (RSI) < (RSI_MA)
🅰️ ADX
🟢 LONG = (+DI) > (-DI) and (ADX) > (Treshold)
🔴 SHORT = (+DI) < (-DI) and (ADX) > (Treshold)
🥊 SAR
🟢 LONG = (close) > (SAR)
🔴 SHORT = (close) < (SAR)
☁️ Cloud
🟢 LONG = (Cloud A) > (Cloud B)
🔴 SHORT = (Cloud A) < (Cloud B)
☁️ Cloud
🟢 LONG = (Kama) > (Kama )
🔴 SHORT = (Kama) < (Kama )
🌡️ R/F
🟢 LONG = (high) > (UP Range) and (upward) > (0)
🔴 SHORT = (low) < (DOWN Range) and (downward) > (0)
🌡️ R/F
🟢 LONG = (high) > (UP Range)
🔴 SHORT = (low) < (DOWN Range)
📐 S/R
🟢 LONG = (close) > (Resistance)
🔴 SHORT = (close) < (Support)
╭╯MA2️⃣
🟢 LONG = (Cyan Bar MA2️⃣)
🔴 SHORT = (Red Bar MA2️⃣)
╭╯MA2️⃣
🟢 LONG = (close) > (MA2️⃣)
🔴 SHORT = (close) < (MA2️⃣)
╭╯MA2️⃣
🟢 LONG = (Positive MA2️⃣)
🔴 SHORT = (Negative MA2️⃣)
__________________________________________________________
🎯 TP / SL 🛑
__________________________________________________________
🎯 TP: 1.5 ％
🛑 SL: 2.0 ％
__________________________________________________________
🪄 UNIQUE FEATURES OF THIS STRATEGY
____________________________________
1) 𝄜 Table Backtest for Mobile.
2) 𝄜 Table Backtest for Computer.
3) 𝄜 Table Backtest for Computer & Annual Performance.
4) 𝄜 Live Entry Conditions.
1) 𝄜 Table Backtest for Mobile.
2) 𝄜 Table Backtest for Computer.
3) 𝄜 Table Backtest for Computer & Annual Performance.
4) 𝄜 Live Entry Conditions.
_____________________________
𝄜 BACKTEST / PERFORMANCE 𝄜
_____________________________
• Net Profit: +634.47%, Maximum Drawdown: -18.44%.
🪙 PAIR / TIMEFRAME ⏳
🪙 PAIR: BINANCE:BTCUSDT.P
⏳ TIME: 4 hours (240m)
✅ ON ☑️ OFF
✅ LONG
✅ SHORT
🎯 TP / SL 🛑
🎯 TP: 1.5 (％)
🛑 SL: 2.0 (％)
⚙️ CAPITAL MANAGEMENT
💸 Initial Capital: 10000 $ (TradingView)
💲 Order Size: 10 ％ (Of Equity)
🚀 Leverage: 10 x (Exchange)
💩 Commission: 0.03 ％ (Exchange)
📆 BACKTEST
🗓️ Start: Setember 24, 2019
🗓️ End: November 21, 2025
🗓️ Days: 2250
🗓️ Yers: 6.17
🗓️ Bars: 13502
📊 PERFORMANCE
💲 Net Profit: + 63446.89 $
🟢 Net Profit: + 634.47 ％
💲 DrawDown Maximum: - 10727.48 $
🔴 DrawDown Maximum: - 18.44 ％
🟢 Total Closed Trades: 1042
🟡 Percent Profitable: 63.92 ％
🟡 Profit Factor: 1.247
💲 Avg Trade: + 60.89 $
⏱️ Avg # Bars in Trades
🕯️ Avg # Bars: 4
⏳ Avg # Hrs: 15
✔️ Trades Winning: 666
❌ Trades Losing: 376
✔️ Maximum Consecutive Wins: 11
❌ Maximum Consecutive Losses: 7
📺 Live Performance : br.tradingview.com
• Use this strategy on the recommended pair and timeframe above to replicate the tested results.
• Feel free to experiment and explore other settings, assets, and timeframes.
Simplified WMA Ribbon · Majority Rule StrategyThis strategy is a simplified WMA-ribbon “majority rule” system. It compares five fast WMAs (10–30) with five slow WMAs (70–90) and counts how many bullish or bearish pairs are strongly separated by a small ε-buffer. A long (short) position is opened only when a bullish (bearish) majority is reached and closed when that majority weakens or an opposite majority appears. Position size is calculated from a fixed USD amount and leverage, candles are colored by current position, and a mini dashboard shows the number of bullish/bearish pairs and the current status (LONG / SHORT / FLAT).
GraalSTRATEGY DESCRIPTION — “GRAAL”
GRAAL is an advanced algorithmic crypto-trading strategy designed for trend and semi-trend market conditions. It combines ATR-based trend/flat detection, dynamic Stop-Loss and multi-level Take-Profit, break-even (BE) logic, an optional trailing stop, and a “lock-on-trend” mechanism to hold positions until the market structure truly reverses.
The strategy is optimized for Binance, OKX and Bybit (USDT-M and USDC-M futures), but can also be used on spot as an indicator.
Core Logic
Trend Detection — dynamic trend zones built using ATR and local high/low structure.
Entry Logic — positions are opened only after trend confirmation and a momentum-based local trigger.
Exit Logic:
fixed TP levels (TP1/TP2/TP3),
dynamic ATR-based SL,
break-even move after TP1 or TP2,
optional trailing stop.
Lock-on-Trend — positions remain open until an opposite trend signal appears.
Noise Protection — flat filter disables entries during low-volatility conditions.
Key Advantages
Sophisticated and reliable risk-management system.
Minimal false entries due to robust trend filtering.
Optional trailing logic to maximize profit during strong directional moves.
Works well on BTC, ETH and major altcoins.
Easily adaptable for various timeframes (1m–4h).
Supports full automation via OKX / WunderTrading / 3Commas JSON alerts.
Recommended Use Cases
Crypto futures (USDT-M / USDC-M).
Intraday trading (5m–15m–1h).
Swing trading (4h–1D).
Fully automated signal-bot execution.
Important Notes
This is an algorithmic strategy, not financial advice.
Strategy Tester performance may differ from real execution due to liquidity, slippage and fees.
Always backtest and optimize parameters for your specific market and asset.
Recommended Settings: LONG only, no TP, no SL, Flat Policy: Hold, TP3 Mode: Trend, Trailing Stop 1.2%, Fixed size 100 USD, Leverage 10×, ATR=14, HH/LL=36.
Inyerneck Sniper Engine v4.2 — FINAL WORKING 2025Aggressive momentum sniper for pennies. Fires on volume + EMA snaps. Use small size. Alerts ready.
