BTC Momentum Strategy - RSI & Stoch RSI Entry and EMA ExitBTC Momentum Strategy: RSI & Stoch RSI Entry with EMA Exit
This strategy is designed to identify potentially strong entry points for Bitcoin (BTC) during periods of shifting momentum and then ride the trend until it shows signs of weakness. It's a straightforward, long-only strategy, meaning it only looks for opportunities to buy and then sell for a profit.
How It Works:
The strategy combines a few classic indicators to make its decisions. Think of it as a two-step confirmation system for buying, with a simple rule for selling.
1. The Buy Signal (Green Triangle)
To generate a buy signal, the strategy looks for two things to happen at the same time:
RSI Confirmation: It first waits for the Relative Strength Index (RSI) to show signs of bullish momentum. Specifically, it's looking for the RSI line to cross above its own moving average, suggesting that strength is starting to build from a lower level. This helps catch moves as they begin to turn positive.
Stochastic RSI Confirmation: As an extra layer of confirmation, it also checks the Stochastic RSI. This helps filter out weaker signals and confirm that momentum is truly shifting upwards from an oversold or "bottomed-out" condition.
When both of these conditions are met, a green "buy" triangle will appear below the candle, and the strategy will enter a long position.
2. The Sell Signal (Red Triangle)
The exit rule is simple and designed to let your winners run while protecting you when the trend reverses.
* EMA-Based Exit: The strategy plots an orange line on your chart, which is an Exponential Moving Average (EMA). The strategy will hold the position as long as the price stays above this line. If a candle closes *below* the orange EMA line, it's taken as a sign that the short-term trend is weakening, and the strategy will close the position to lock in profits or cut losses. A red "sell" triangle will appear above that candle.
Best Use:
This strategy was built with Bitcoin in mind and tends to perform best on higher timeframes like the Weekly charts. It aims to capture major swings rather than small, quick scalps.
You can adjust all the settings for the RSI, Stochastic RSI, and the Exit EMA to fine-tune the strategy to your own trading style.
Göstergeler ve stratejiler
MACD Aspray Hybrid Strategy The MACD Aspray Hybrid Strategy is a trend-following trading system based on a modified version of the MACD indicator.
MACD Aspray Hybrid Strategy The MACD Aspray Hybrid Strategy is a trend-following trading system based on a modified version of the MACD indicator.
Daily Breakout Strategy
🧠 Daily Breakout Strategy • No Repaint
This is a non-repainting backtestable strategy built on clean breakout logic using daily pivot-based levels. It executes one trade per day, following simple rules: wait for breakouts, aim for the target, and log whether it hits.
Designed for traders who want uncluttered, rule-based backtests using price action without lagging indicators or repaint tricks.
🔍 Strategy Logic:
The system calculates daily key levels based on previous day's high, low, and close:
Pivot (P) = (High + Low + Close) / 3
Buy Entry (r1) = P + 0.382 × (High - Low)
Buy TP (r2) = P + 0.618 × (High - Low)
Sell Entry (s1) = P – 0.382 × (High - Low)
Sell TP (s2) = P – 0.618 × (High - Low)
✅ Entry & Exit Rules (Non-Repainting):
🔹 A Buy trade is entered when price closes above r1, confirmed on the next bar.
🔹 A Sell trade is entered when price closes below s1, also confirmed.
🚫 Only 1 signal per day is allowed.
✅ Each trade targets its respective TP level (r2 or s2).
If TP is hit during the session, the trade closes as a win.
If TP is not hit by end of day, the system registers a loss.
⛔ No repainting — all entries are based on closed candles.
📊 Performance Table (Built-in):
A live table tracks and displays:
🟢 Buy/Sell Status (e.g., "Buy Active", "Sideways")
📌 Current Entry/TP Prices
📅 Today’s Breakout Levels
📈 Buy Win % and Sell Win %
📊 Total Accuracy over last N trades (default: 300)
This helps users understand edge, expectancy, and directional bias.
🧪 Backtesting Tips:
Works best on intraday timeframes like 5m, 15m, or 1H.
You may combine it with your own risk management, filters, or alerts.
Results are accurate for what this strategy simulates: 1 entry per day, no SL, TP-only logic.
⚙️ Strategy Settings:
🔧 Accuracy Lookback: Number of trades to track for % win stats.
🎯 Default Quantity: 100% equity by default — adjust to suit your model.
💡 No leverage, pyramiding, or position sizing built in — this is kept clean and logic-focused.
🔒 Access Info:
This strategy is FREE to use
🔐 Source code is locked to protect stability and performance
You can use this for backtesting, education, and signal modeling — no payment required.
💬 Feedback Welcome!
If you want this script extended with:
Stop Loss
Trailing Exit
Risk Management
Alert Conditions
...just leave a comment or message. This script is built to grow with the community!
📈 Add it to your chart, study the clean stats, and use it to model your own breakout logic with confidence.
Liquidity+FVG+OB Strategy (v6)How the strategy works (summary)
Entry Long when a Bullish FVG is detected (optionally requires a recent Bullish OB).
Entry Short when a Bearish FVG is detected (optionally requires a recent Bearish OB).
Stop Loss and Take Profit are placed using ATR multiples (configurable).
Position sizing is fixed contract/lot size (configurable).
You can require OB confirmation (within ob_confirm_window bars).
Alerts still exist and visuals are preserved.
EMA CROSS STRATEGY MAXTRA ENTRY LOGIC
Long Entry (Buy Signal):
Condition: Short EMA crosses above Long EMA (Golden Cross)
Interpretation: A potential upward trend is beginning
Short Entry (Sell Signal):
Condition: Short EMA crosses below Long EMA (Death Cross)
Interpretation: A potential downward trend is beginning
EXIT LOGIC
There are a few options depending on the style of strategy:
Option 1: Opposite Crossover
Exit Long: When Short EMA crosses below Long EMA
Exit Short: When Short EMA crosses above Long EMA
This method keeps you in the trade until the trend reverses.
Option 2: Fixed Stop Loss / Take Profit
Exit trade when a profit target or stop loss is hit
Example: 2% stop loss and 4% take profit
Note : In Properties, go to Initial Margin. Add one more zero to get the backtest results for futures trades. For spot, use it as it is.
Stochastic Divergence StrategyBackground bars:
Bearish
gradient from slightly bearish divergence to strong bearish divergence for red and a double bounce for pink
Bullish
gradient from slightly bearish divergence to strong bearish divergence for green and a double bounce for yellow
removable buy and sell signals in options
G. Santostasi Bitcoin Power Law StrategyG. Santostasi Bitcoin Power Law Strategy
Overview
The "G. Santostasi Bitcoin Power Law Strategy" is a TradingView strategy script built upon the foundational Bitcoin Power Law Theory by physicist Giovanni Santostasi.
Unlike the companion Monte Carlo indicator, this strategy focuses on generating actionable buy entry and exit signals for trading Bitcoin, leveraging the normalized "Daily Slopes" metric to detect deviations from the long-term power-law trend. It employs two moving windows to compute local means (mu) of the Daily Slopes—a short-term 3-day window for responsive signals and a longer 2-week (14-day) window for establishing baseline bands. By comparing the short-term mu against deviation bands derived from the longer window's parameters, the strategy identifies entry points during undervalued dips and exit points during overvalued peaks. This approach capitalizes on Bitcoin's scale-invariant behavior, where price follows a power law
P(t)= c t^n, with n~5.9.
since the Genesis Block, resulting in diminishing but predictable returns. Backtested over Bitcoin's full history, the strategy boasts a 77% winning rate and a profit factor of 3.2, making it a robust tool for trend-following with mean-reversion elements. It emphasizes Bitcoin's long-term stability while navigating short-term oscillations, treating cycles as temporary deviations from the core power-law "DNA.
"Core Concept: Daily Slopes
The strategy inherits the Daily Slopes metric from the power-law framework, which normalizes daily logarithmic returns to reveal a stable local slope that oscillates around the global value of ~5.9.Definition and Calculation:
Daily log returns: log(P2/P1)\, where P2 and P1 are consecutive closing prices.
Normalization: Divide by log((t+1)/t), where ( t ) is days since the Genesis Block, yielding:
Daily Slope=log(P2/P1)log((t+1)/t).
This produces a "local n" that remains stable over time, with no long-term drift observed in Bitcoin's 16+ years of data. The metric accounts for diminishing returns, showing constant relative volatility in recent years despite absolute price stabilization.
Distribution and Parameters:
Daily Slopes are fitted to a t-location scale distribution over moving windows, estimating:μ (mu): The location/mean, stable around 5.9 globally.
σ (sigma): Scale/volatility measure.
ν (nu): Degrees of freedom for tail heaviness.
For the strategy, focus is on mu and sigma from the windows, enabling deviation-based signals.
Strategy Logic: Dual Moving Window Mus and Deviation Bands
The strategy computes two mus via rolling fits to the t-distribution:
Short Window mu (3 days): A fast-moving average of Daily Slopes, sensitive to immediate price action for timely signals.
Long Window mu (2 weeks/14 days): A slower baseline, capturing medium-term trends and providing stability.
Deviation bands are derived from the long window's mu and sigma:
Upper Band: Long mu + Long sigma
Lower Band: Long mu - Long sigma
These bands represent 1-standard-deviation ranges around the longer-term mean, highlighting overbought and oversold conditions relative to the power-law trend. The short mu acts as a "signal line," crossing the bands to trigger trades.
Plotting:
Short mu: Responsive line for crossovers.
Long mu: Central baseline.
Bands: Upper (+σ) and lower (-σ) lines from the long window.
Additional elements: Raw Daily Slopes and strategy signals (arrows for entries/exits).
Entry and Exit Rules:
The strategy generates long-only signals (buy/sell) based on crossovers, assuming a single-position approach without leverage or shorting:
Buy Entry: Triggered when the short-window mu crosses above the lower band (long mu - long sigma). This detects potential local minima, signaling undervaluation and a reversion to the power-law mean.
Sell Exit: Triggered when the short-window mu meets or crosses below the upper band (long mu + long sigma). This identifies local maxima, indicating overvaluation and a potential pullback.
Trade Management:
No stop-loss or take-profit hardcoded; users can add via TradingView settings.
Positions close on exit signals, with re-entry on the next valid buy.
Filters for false signals: Optional confirmation from global slope (e.g., only trade if long mu > 5.0) to align with bullish regimes.
This crossover mechanic blends momentum (short mu) with mean-reversion (bands), exploiting Bitcoin's oscillatory nature around the power law without predicting bubbles or crashes explicitly.
Performance Metrics:
Backtested on BTCUSD daily data from the Genesis Block to present (assuming continuous updates):Winning Rate: 77% – A high hit rate due to the strategy's focus on statistically stable deviations.
Profit Factor: 3.2 – Gross profits are 3.2 times gross losses, reflecting asymmetric upside from power-law reversion.
Additional Stats (hypothetical based on historical fits): Average trade duration ~30-60 days; drawdown <20% in most cycles; outperforms buy-and-hold in volatile periods by avoiding peaks.
Caveats: Past performance is not indicative of future results. The strategy shines in trending markets but may underperform in prolonged sideways action. Transaction costs (e.g., fees, slippage) not included in base metrics.
Usage Notes Inputs: Customize window lengths (default: 3 days short, 14 days long), global slope (5.9), and signal thresholds. Enable alerts for entries/exits.
Visuals: Strategy overlays on log-scale BTCUSD charts; use with volume or RSI for confirmation.
Limitations: Designed for spot trading; not optimized for derivatives or high-frequency. Assumes power-law persistence—major regime shifts (e.g., adoption plateaus) could impact efficacy.
Extensions: Adapt for other power-law metrics like network addresses or hash rate for multi-signal confirmation.
This strategy operationalizes Santostasi's insights into a practical trading system, prioritizing data-driven decisions over speculation.
Diamond-Triangle Strategy - Dynamic Trailing v2This had an adaptive exit strategy added with diamond entries not working well
Dwaggy Scalping Trio (VWAP + EMA + RSI)First attempt at pine script this is a scalping indicator that combines VWAP, EMA, and RSI to signal entry/exit for scalping lower time frames
Quantura - Quantified Price Action StrategyIntroduction
“Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices.
Originality & Value
The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of:
Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity.
Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs.
RSI filter: Can be set to normal or aggressive, confirming momentum before trades.
Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies.
EMA filter: Aligns trades with the broader market trend.
Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions.
This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow.
Functionality & Indicators
Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap.
Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection.
RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness.
FVG filter: Adds validation by requiring price interaction with inefficiency zones.
EMA filter: Ensures longs are above EMA and shorts below EMA.
Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status.
Parameters & Customization
Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options.
Liquidity filter: Mode (Run or Sweep), display, and swing length.
RSI: Enable/disable, length, and style (normal or aggressive).
Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles.
EMA: Length, enable/disable, and visualization.
Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing.
Visualization: Custom candle coloring and optional overlay for better clarity.
Default Properties (Strategy Settings)
Initial Capital: 10,000 USD
Position Size: 100% of equity per trade (backtest default)
Commission: 0.1%
Slippage: 1
Pyramiding: 0 (only one position at a time)
Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%.
Backtesting & Performance
Backtests on XPTUSD over 2.5 years with the default settings produced:
129 trades
73.64% win rate
Profit factor: 2.6
Maximum drawdown: 18.2%
These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (129) is sufficient for statistical analysis, results may vary across markets and timeframes.
Risk Management
Three configurable take-profit levels with percentage allocation.
Initial stop-loss based on user-defined percentage.
Dynamic stop-loss that adjusts with market movement.
Break-even logic that shifts stops to entry after predefined gains.
Position sizing based on risk percentage of equity.
This framework allows both conservative and aggressive configurations, depending on user preference.
Limitations & Market Conditions
Works best in volatile and liquid markets such as crypto, metals, indices, and FX.
May produce false signals in low-volume or sideways environments.
Unexpected news or macro events can override technical conditions.
Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use.
Usage Guide
Add “Quantura – Quantified Price Action Strategy” to your chart.
Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe.
Configure risk management: take-profits, stop-loss, and risk-per-trade percentage.
Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions.
Optimize parameters before applying the strategy to different markets.
Author & Access
Developed 100% by Quantura. Published as an Invite-Only script. Access is available upon request via the Author’s Instructions field.
Important
This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Big Swing Strategy - for swing trading The Big Swing strategy is designed to capture major directional moves by combining momentum signals with trend confirmation . It blends a long-lookback RSI with a smoothed Stochastic to detect extreme overbought/oversold conditions, while the Supertrend indicator ensures trades align with the prevailing market bias.
Bullish setups trigger when the Stochastic K dips below the lower threshold and Supertrend confirms an uptrend.
Bearish setups trigger when the Stochastic D rises above the upper threshold with Supertrend confirming a downtrend.
Optional stop-loss and take-profit levels help manage risk and lock in gains.
Visual entry/exit markers, alerts, and trade-state backgrounds make it easy to follow in real time.
This strategy is suited for traders who want to ride strong swings while filtering noise with robust trend confirmation.
MTF Regime + Breakout-Pullback by HarshMTF BTC regime filter + trend filter, Donchian breakout after a pullback, ATR‑based stop, 2 profit targets, trailing runner, and pyramiding into 3 tranches.
Elite Momentum Scalper🎯 Perfect For
Scalpers Who Want:
Quick In-and-Out Trades: Designed for 1-15 minute timeframes but works very well on the higer timeframes. Especiall Designed for : Indices ie NAS100 SPX in the New York Session but does work in London session also.
High Win Rate: Multiple confirmations reduce false signals
Consistent Risk: Same risk per trade, every trade
Clean Charts: No indicator spaghetti, just clear signals
Best Markets: Indices ie NAS100 SPX New York Session
Forex Majors: EUR/USD, GBP/USD, USD/JPY
Precious Metals: XAU/USD (Gold), XAG/USD (Silver)
Crypto: BTC/USD, ETH/USD (works 24/7)
Indices: SPX, NAS, DAX during active sessions
Optimal Timeframes:
Primary: 5-minute, 15-minute charts
Works On: Any timeframe (auto-adjusts)
Session-Aware: Best during London/NY overlap
🚨 Built-in Alerts
Never miss a trade:
Entry Alerts: "LONG ENTRY at 1.2345 SL: 1.2300 TP: 1.2400"
Exact Levels: Includes entry, stop, and target prices
Mobile Friendly: Works with TradingView mobile alerts
💡 Pro Tips for Best Results
Setup Recommendations:
Start Conservative: Begin with 1% risk per trade
Respect Sessions: Best results during London/NY hours
Don't Override: Let the cooldown system work
Monitor Dashboard: Keep an eye on daily trade count
Backtest First: Test on historical data before live trading
Risk Management:
Never risk more than you can afford to lose
Use proper position sizing (built-in calculator)
Respect the stop losses (they're there for a reason)
Monitor during high-impact news events
🏆 Why The Elite One?
Based on Fabio Valentini's proven #1 scalper methodology, this isn't just another indicator—it's a complete trading system that:
✅ Eliminates Guesswork: Exact entry, stop, and target levels
✅ Manages Risk: Built-in position sizing and risk management
✅ Prevents Overtrading: Smart cooldown system
✅ Adapts to Markets: ATR-based levels adjust to volatility
✅ Saves Time: All information in one clean dashboard
✅ Works Anywhere: Any market, any timeframe
✅ Stays Clean: No chart clutter, just actionable signals
Join thousands of traders who've upgraded their scalping game with the world's #1 scalper's methodology, refined into institutional-grade precision with retail-friendly execution.
⚠️ Important Disclaimers
Past performance does not guarantee future results
Trading involves substantial risk of loss
Test thoroughly on demo accounts first
Consider broker spreads in your calculations
Not financial advice - trade at your own risk
📈 Ready to Transform Your Trading?
Add The Elite One to your chart and experience the difference that professional-grade trading tools based on proven scalping methodology can make.
Remember: The best traders don't just follow signals—they understand their tools. Take time to learn the system, backtest thoroughly, and always trade responsibly.
Happy Trading! 🚀
The Elite One - Based on Fabio Valentini's #1 Scalper Methodology ⚡️
Pivot SuperTrend Auto-Opt + WFO + MultiObj + Filter/Diag# Pivot SuperTrend (NetProfit Auto-Optimization) — Summary & Quick Start
## What this strategy is
A self-optimizing **SuperTrend-style** strategy for TradingView Pine v6 that:
- builds a **walk-forward, net-profit optimizer** directly on the chart,
- adapts its trailing stop/entry logic to **market regime** and **volatility**, and
- exposes a **filter/gate suite** so you can dial aggressiveness vs. noise without breaking auto-optimization.
Default tuning: **Bybit ETHUSDT Perpetual, 30m** (works elsewhere once tuned).
---
## Core logic (high level)
### 1) SuperTrend backbone (with Center/Pivots)
- **Center line**: smoothed running pivot from `ta.pivothigh/low`.
- **SuperTrend bands**: `Center ± Factor × ATR(length)` with a carry rule to reduce whipsaws.
- **Trend state**: `+1` above band, `-1` below band.
- **Flip**: trend change; can require **1-bar confirmation**.
### 2) Adaptive smoothing (AMA of ST)
- Performance-weighted **alpha** smooths the trailing stop.
- Alpha clamped to `alpha_min…alpha_max` using optimizer’s fitness.
### 3) On-chart net-profit optimizer (walk-forward)
- Grid of parameters:
- ATR Length `len` (min…max…step)
- ATR Factor `F` (min…max…step)
- Performance memory `A` (min…max…step)
- Each grid point is paper-traded **each bar** including fees/slippage → **fitness = net profit EMA**.
- Every `opt_interval` bars the **best** candidate is activated (with hysteresis).
- Optional: apply only **ATR margin** gate inside the optimizer for speed/stability.
### 4) Regime detection & anti-chop
- Custom **ADX** + **Center slope** to classify **trend** vs **range**.
- Adaptive thresholds in range regime (distance-to-center, ST-near-center block, etc.).
- Optional **ATR fast/slow ratio** gate.
- Other tools: **min bars since flip**, **hold bars after flip**, **distance to center**, **ST near center** block.
### 5) Entry logic
- **Immediate on flip** or **1-bar confirm**.
- Must pass the **Filter Suite** (toggleable gates):
- ATR-margin cross (hard cross or wick reject)
- Trend Regime (require trend)
- Hold-after-flip
- Distance-to-center
- ST-near-center block
- Volatility ratio (ATR fast/slow)
- Min bars since flip (flip cooldown)
- Daily trade cap & post-loss cooldown
- Trading session window
### 6) Starter preset (failsafe)
- Lenient defaults so trades start quickly to build warm-up data; then you can tighten gates.
### 7) Position management
- Strategy entries for “LONG” / “SHORT”.
- Optional **50% take-profit on Center** (“usecenter”).
- **Only-Long** mode supported with separate exit logic if regime turns bearish.
### 8) Risk controls
- **Max trades per day**, **cooldown bars after loss**, **session window**.
- Optional **bar coloring**, **trend shading**, **signal markers**.
- **Diagnostics** labels show which gate blocked an entry (letters `M T H D N V F C CD S`).
### 9) Alerts & Bybit webhook
- Use alert condition: **Any alert() function call**.
- Fires `"LONG_CONFIRMED"` / `"SHORT_CONFIRMED"`.
---
## Inputs overview
- **Pivot / Center**: pivot length; show pivots & center.
- **Visual**: line widths, bar colors, shading; warm-up bars.
- **Execution / Costs**: fee (bps), slippage (bps), “Only long”, 50% center-close.
- **Auto-Optimize**: grids for `len`, `F`, `A`, interval, memory, acceptance floor.
- **Signal Controls**: 1-bar confirm, ATR margin, min bars since flip.
- **Anti-Chop**: distance to center, hold bars, slope len, ST-near-center ATR, ATR slow len & ratio.
- **Trend Regime**: ADX len/threshold, center slope threshold, “require trend”.
- **Risk Gates**: max trades/day, loss cooldown bars.
- **Session**: optional 07:00–22:00 UTC filter.
- **Diagnostics**: show gate diagnostics labels.
- **Filter Suite**: toggle each gate; optional “apply margin to optimizer”.
- **Starter preset** selector.
---
## Plots & UI
- **Adaptive SuperTrend** (active candidate),
- **PP Center** (optional),
- **Trend shading** (price vs ST zone),
- **Entry/Exit markers** (triangles),
- **Diagnostics** text labels (optional).
---
## Webhook notes (Bybit v5)
If you use a direct Bybit webhook:
- **Symbol**: TradingView may emit `ETHUSDT.P`. Bybit wants `ETHUSDT`. Your relay should **strip `.P`**.
- **Side**: TV provides `buy/sell`. Bybit expects `Buy/Sell` → normalize casing in the relay.
- **Reduce-only**: mark exits and partial closes reduce-only to avoid reversals in Hedge mode.
- **Market orders**: pass `"orderType":"Market"`; ignore price or set to `"marketPrice"` if your relay requires it.
**Entry (Market)**
```json
{
"exchange": "BYBIT",
"category": "linear",
"symbol": "{{ticker}}",
"side": "{{strategy.order.action}}",
"orderType": "Market",
"qty": "{{strategy.order.contracts}}",
"reduceOnly": false,
"timestamp": "{{timenow}}",
"clientOrderId": "pst_{{strategy.order.id}}_{{timenow}}"
}
AR Alerts Basic 🤖A non-repainting, ATR-based trailing stop strategy and session-based trading filters.
Features:
Dynamic buy/sell trailing stops using ATR for stable exits.
EMA exit for remaining positions to lock in profits.
Time session filters: trade only during defined market hours.
Trend detection using EMA50/EMA100 coloring.
Backtest dashboard Table showing total trades, win rate, P&L, growth, profit factor, and max drawdown. can be uncheck from Style Tab.
Fully non-repainting signals for reliable historical testing.
Perfect for traders who want stable signals, trailing stops, and a clean backtest summary in one indicator.
@infonatics
Hosoda’s CloudsMany investors aim to develop trading systems with a high win rate, mistakenly associating it with substantial profits. In reality, high returns are typically achieved through greater exposure to market trends, which inevitably lowers the win rate due to increased risk and more volatile conditions.
The system I present, called “Hosoda’s Clouds” in honor of Goichi Hosoda , the creator of the Ichimoku Kinko Hyo indicator, is likely one of the first profitable systems many traders will encounter. Designed to capture trends, it performs best in markets with clear directional movements and is less suitable for range-bound markets like Forex, which often exhibit lateral price action.
This system is not recommended for low timeframes, such as minute charts, due to the random and emotionally driven nature of price movements in those periods. For a deeper exploration of this topic, I recommend reading my article “Timeframe is Everything”, which discusses the critical importance of selecting the appropriate timeframe.
I suggest testing and applying the “Hosoda’s Clouds” strategy on assets with a strong trending nature and a proven track record of performance. Ideal markets include Tesla (1-hour, 4-hour, and daily), BTC/USDT (daily), SPY (daily), and XAU/USD (daily), as these have consistently shown clear directional trends over time.
Commissions and Configuration
Commissions can be adjusted in the system’s settings to suit individual needs. For evaluating the effectiveness of “Hosoda’s Clouds,” I’ve used a standard commission of $1 per order as a baseline, though this can be modified in the code to accommodate different brokers or preferences.
The margin per trade is set to $1,000 by default, but users are encouraged to experiment with different margin settings in the configuration to match their trading style.
Rules of the “Hosoda’s Clouds” System (Bullish Strategy)
This strategy is designed to capture trending movements in bullish markets using the Ichimoku Kinko Hyo indicator. The rules are as follows:
Long Entry: A long position is triggered when the Tenkan-sen crosses above the Kijun-sen below the Ichimoku cloud, identifying potential reversals or bounces in a bearish context.
Stop Loss (SL): Placed at the low of the candle 12 bars prior to the entry candle. This setting has proven optimal in my tests, but it can be adjusted in the code based on risk tolerance.
Take Profit (TP): The position is closed when the Tenkan-sen crosses below the bottom of the Ichimoku cloud (the minimum of Senkou Span A and Senkou Span B).
Notes on the Code
margin_long=0: Ideal for strategies requiring a fixed position size, particularly useful for manual entries or testing with a constant capital allocation.
margin_long=100: Recommended for high-frequency systems where positions are closed quickly, simulating gradual growth based on realized profits and reflecting real-world broker constraints.
System Performance
The following performance metrics account for $1 per order commissions and were tested on the specified assets and timeframes:
Tesla (H1)
Trades: 148
Win Rate: 29.05%
Period: Jan 2, 2014 – Jan 6, 2020 (+172%)
Simple Annual Growth Rate: +34.3%
Trades: 130
Win Rate: 30.77%
Period: Jan 2, 2020 – Sep 24, 2025 (+858.90%)
Simple Annual Growth Rate: +150.7%
Tesla (H4)
Trades: 102
Win Rate: 32.35%
Period: Jun 29, 2010 – Sep 24, 2025 (+11,356.36%)
Simple Annual Growth Rate: +758.5%
Tesla (Daily)
Trades: 56
Win Rate: 35.71%
Period: Jun 29, 2010 – Sep 24, 2025 (+3,166.64%)
Simple Annual Growth Rate: +211.5%
BTC/USDT (Daily)
Trades: 44
Win Rate: 31.82%
Period: Sep 30, 2017 – Sep 24, 2025 (+2,592.23%)
Simple Annual Growth Rate: +324.8%
SPY (Daily)
Trades: 81
Win Rate: 37.04%
Period: Jan 23, 1993 – Sep 24, 2025 (+476.90%)
Simple Annual Growth Rate: +14.3%
XAU/USD (Daily)
Trades: 216
Win Rate: 32.87%
Period: Jan 6, 1833 – Sep 24, 2025 (+5,241.73%)
Simple Annual Growth Rate: +27.1%
SPX (Daily)
Trades: 217
Win Rate: 38.25%
Period: Feb 1, 1871 – Sep 24, 2025 (+16,791.02%)
Simple Annual Growth Rate: +108.1%
Conclusion
With the “ Hosoda’s Clouds ” strategy, I aim to showcase the potential of technical analysis to generate consistent profits in trending markets, challenging recent doubts about its effectiveness. My goal is for this system to serve as both a practical tool for traders and a source of inspiration for the trading community I deeply respect. I hope it encourages the creation of new strategies, fosters creativity in technical analysis, and empowers traders to approach the markets with confidence and discipline.
FractalReversalStrategyFiltered(ETH 5min) The profit that is shown in the strategy report uses a capital of 240 USD with 10x leverage. Only use this strategy in ETHUSD (5 MIN timeframe).
FractalReversalStrategyFiltered(SOL 5min) - ZERO FALSE TRADEThe profit that is shown in the strategy report uses a capital of 240 USD with 10x leverage. Only use this strategy in SOLUSD (5 MIN timeframe).
AI - Gaussian Channel Strategy AI – Gaussian Channel Strategy is a long-only swing trading strategy designed for Bitcoin and other assets on daily charts. It combines an adaptive Gaussian Channel with Supertrend and Stochastic RSI filters to identify potential bullish breakouts or pullback entries. The channel defines trend direction and volatility, while the Stochastic RSI provides momentum confirmation. Positions are opened only when the price closes above the channel’s upper band under favorable momentum conditions, and are closed when the price crosses back below the band.
This script is intended for educational and research purposes. Parameters such as poles, period length, ATR factor, and RSI settings can be adjusted to fit different markets and timeframes.
Disclaimer: This script does not guarantee profits and should not be considered financial advice. Past performance is not indicative of future results. Trading involves risk, and you are solely responsible for your own decisions and outcomes.
TrendIsYourFriend Strategy (SPY,IWM,VYM,XLK,SPXL,BTC,GOLD,VT...)Personal disclaimer
Don’t trust this strategy. Don’t trust any other model either just because of its author or a backtest curve. Overfitting is an easy trap, and beginners often fall into it. This script isn’t meant to impress you. It’s meant to survive reality. If it does, maybe it will raise questions and you’ll remember it.
Legal disclaimer
Educational purposes only. Not financial advice. Past performance is not indicative of future results.
Strategy description
Long-only, trend-based logic with two entry types (trend continuation or excess-move reversion), dynamic stop-losses, and a VIX filter to avoid turbulent markets.
Minimal number of parameters with enough trades to support robustness.
For backtest, each trade is sized at $10,000 flat (no compounding, to focus on raw model quality and the regularity of its results over time).
Fees = $0 (neutral choice, as brokers differ).
Slippage = $0, deliberate choice: most entries occur on higher timeframes, and some assets start their history on charts at very low prices, which would otherwise distort results.
What makes this script original
Beyond a classical trend calculation, both excess-move entries and dynamic stop-loss exits also rely on trend logic. Except for the VIX filter, everything comes from trend functions, with very few parameters.
Pre-configurations are fixed in the code, allowing sincere performance tracking across a dozen cases over the medium to long term.
Allowed
SPY (ARCA) — 2-hour chart: S&P 500 ETF, most liquid equity benchmark
IWM (ARCA) — Daily chart: Russell 2000 ETF, US small caps
VYM (ARCA) — Daily chart: Vanguard High Dividend Yield ETF
XLK (ARCA) — Daily chart: Technology Select Sector SPDR
SPXL (ARCA) — Daily chart: 3× leveraged S&P 500 ETF
BTCUSD (COINBASE) — 4-hour chart: Bitcoin vs USD
GOLD (TVC) — Daily chart: Gold spot price
VT (ARCA) — Daily chart: Vanguard Total World Stock ETF
PG (NYSE) — Daily chart: Procter & Gamble Co.
CQQQ (ARCA) — Daily chart: Invesco China Technology ETF
EWC (ARCA) — Daily chart: iShares MSCI Canada ETF
EWJ (ARCA) — Daily chart: iShares MSCI Japan ETF
How to use and form an opinion on it
Works only on the pairs above.
Feel free to modify the input parameters (slippage, fees, order size, margins, …) to see how the model behaves under your own conditions
Compare it with a simple Buy & Hold (requires an order size of 100% equity).
You may also want to look at its time-in-market — the share of time your capital is actually at risk.
Finally, let me INSIST on this : let it run live for months before forming an opinion!
Share your thoughts in the comments 🚀 if you’d like to discuss its live performance.
💎🔺⚫ Diamond-Triangle-Circle StrategyUpgrade the high low low high strat to cut out signal noise and flat markets dont take the black circles they eat profits
