ADX GatekeeperADX Gatekeeper is an original strategy that combines three classic filters to improve trend-following accuracy and avoid choppy markets.
Combines RSI, OBV, and ADX filters to catch stronger trends and avoid sideways markets. RSI confirms momentum extremes, OBV confirms volume flow, and ADX filters low-trend conditions. Fully configurable for different market conditions.
RSI Filter: Avoids overbought/oversold traps by requiring RSI < 35 for longs and > 70 for shorts.
OBV Filter: Confirms directional volume with positive OBV changes for longs and negative for shorts.
ADX Filter: Filters out low-volatility sideways conditions by requiring ADX above a configurable threshold (default 45).
The combined conditions aim to identify stronger trend moves while avoiding choppy markets. All filters can be toggled on or off for flexibility.
Default risk: 10% of equity per trade. Users can adjust this.
Ideal for trend traders looking to filter noise and improve entry quality.
Strategy
Ekoparaloji&Strategy1000 USDT
BNB Smart Chain (BEP20) usdt: 0x0abd7ec93ebf0d325f7d731ba2a128e12bf010d3
Contact ekoparaloji@gmail.com
Opens new long trades during gradual declines in volatility, uses TP with average price, and makes high-profit, high-risk trades.
Chiaroscuro Scalp Model A [Signal + Visuals]This indicator is based on the Chiaroscuro Scalp Model A — a precision-based scalping system that identifies high-probability trade setups during the London and New York sessions. It combines daily range expansion, order blocks, fair value gaps, and W/M reversal patterns to generate 20-pip scalping opportunities with clearly plotted stop loss and take profit levels. Ideal for intraday traders seeking structured, rule-based entries.
BTCUSD 3min LA Timezone | USdailyTrade.com### 📈 BTCUSD 3-Minute Opening Range Breakout Strategy (One Trade Per Day – LA Timezone)
This strategy is a **3-minute Opening Range Breakout (ORB)** system designed specifically for **BTCUSD**, optimized for the **Los Angeles trading session**.
It captures early volatility and momentum by identifying the **first 5-minute range** after the market opens (LA time). The system enters:
- 📈 A **long trade** when price breaks above the high of the range
- 📉 A **short trade** when price breaks below the low
(based on clean breakout price action)
---
### 🔑 Key Features:
- ⏱ **Time-based filter**
Trades only during a specific time window (first **30 minutes** after session opens)
- 🎯 **Dynamic Stop-Loss and Take-Profit**
Targets are calculated based on **range size** and **ATR**, adapting to volatility
- 🚫 **One Trade Per Day**
Limits execution to just one high-probability trade per day – no overtrading
- 🔔 **Built-in Buy/Sell Alerts**
Alerts are automatically triggered when a valid **BUY** or **SELL** signal appears
- ⚡ **Built for volatility**
Optimized for the sharp, directional moves commonly seen in BTCUSD during LA open
---
### 👤 Who Is It For?
This script is ideal for **active intraday traders** who want to trade the **BTCUSD opening breakout** with:
- Predefined risk
- Clear entry/exit logic
- **One high-quality signal per day**
- **Real-time alert notifications**
- Automated trade management
---
> 📌 Created by (www.USdailyTrade.com)
> 💡 AI-powered strategies for **Forex**, **U.S. Stocks**, and **Gold**
Institutional Sessions Overlay (Asia/London/NY)Institutional Sessions Overlay is a professional TradingView indicator that visually highlights the main trading sessions (Asia, London, and New York) directly on your chart.
Customizable: Easily adjust session start and end times (including minutes) for each market.
Timezone Alignment: Shift session boxes using the timezone offset parameter so sessions match your chart’s timezone exactly.
Clear Visuals: Colored boxes and optional labels display session opens and closes for fast institutional market structure reference.
Toggle Labels: Show or hide session open/close labels with a single click for a clean or detailed look.
Intuitive UI: User-friendly grouped settings for efficient configuration.
This tool is designed for day traders, institutional traders, and anyone who wants to instantly recognize global session timing and ranges for SMC, ICT, and other session-based strategies.
How to use:
Set your chart to your local timezone.
Use the "Session timezone offset" setting if session boxes do not match actual session opens on your chart.
Adjust the hours and minutes for each session as needed.
Enable or disable labels in the “Display” settings group.
Tip: Use the overlay to spot session highs and lows, volatility windows, and institutional liquidity sweeps.
Market Entropy Strategy V2.5This strategy is an updated version of a market entropy-based trading system. It removes EMA dependencies and introduces two indicators:
1. **Volatility Momentum Index (VMI)**: Measures volatility acceleration for timing entries (from calm to active phases) and exits (at peak chaos).
2. **Volume-Weighted Price Center (VWPC)**: A volume-weighted trend filter using typical price to determine overall market direction.
The strategy enters trades on transitions from low volatility ("calm") to increasing activity, filtered by trend direction. Exits occur when volatility reaches a high "chaos" threshold. It supports long, short, or both directions, with configurable parameters for optimization.
Backtest results depend on market conditions; use with caution and combine with your own analysis. No guarantees of performance.
AmazingTrend - Long OnlyUnlock powerful trend-following logic with this dynamic and fully customizable Pine Script™ strategy, designed for traders who want precision entries, adaptive exits, and beautiful chart visuals.
✅ Key Features:
Long Bias by Default – Designed to ride bullish momentum with intelligent entries and flexible exits.
Optional Short Capability – While optimized for longs, the engine is also fully capable of short-side logic with minor adaptation.
Multiple Entry Modes – Choose between:
Classic – Reversals only
Aggressive – Early trend detection
Conservative – Confirmed trend continuation
Momentum – Powered by ATR and price bursts
Exit Customization – Includes:
Classic – Balanced logic
Quick – Tight risk control
Trailing – Dynamic stop tracking
Time-Based – Scheduled profit-taking
Visual Feedback – Multi-layered trend glow, buy/exit highlights, and a clean on-chart info panel.
Commission + Order Size Logic – Simulate realistic brokerage conditions with configurable cost and size inputs.
🔍 Chart Compatibility:
For the best performance, we recommend:
✅ Heikin Ashi and Renko charts for clarity and noise reduction.
✅ Use Regular Candlestick Charts only on higher timeframes (Daily and above) for clean signals.
❌ Avoid lower timeframes 1second to 5minute it is not built for this.
🧠 Smart Trend Detection:
The strategy detects directional bias using smoothed ATR-based stops and automatically shifts between bullish and bearish regimes. Entry and exit logic responds dynamically to market strength, giving you the edge in both volatile and trending environments.
🧪 Strategy Tested:
Built for 100% portfolio allocation per trade
Designed for realistic backtests with slippage and commission settings backtest results on our page is 0.25 % on buy and sell so total 0.50 %
Works across multiple markets: Crypto, Forex, Stocks. (futures coming later)
📈 Ideal For:
for shorters. investors, long traders, i do not recommend scalping ever but thats up to you.
Swing and momentum setups
Renko & Heikin Ashi fans
beware tradingview dont support alerts on Renko charts.
accurate backtest results that reflect reality if you use it exactly as displayed.
🎁 This Invite-Only script includes lifetime updates and is optimized for Pine Script v5. Contact the author to gain access. we will ofc develop this script feel free to use any version you prefer in the future.
Support & Resistance by O Dinesh BabuThis Script is Specifically Designed to Work with NIFTY, BANKNIFTY & FINNIFTY Indices Only..
For Optimal Results, Please Wait for the 1st 15-Minute Candle to Complete Before Initiating Any Trades..
Wishing All Traders the Very Best in Their Journey..
Warm Regards,
O. Dinesh Babu
Son of Mr. & Mrs. O. Asha Rama Krishna
َUSDJPY - 3min - One Trade Per Day - LA timezone📌 USDJPY - 3min - One Trade Per Day - LA TimeZone
**🔵 High-Confidence Strategy with Over 75% Win Rate**
A minimalistic and consistent breakout trading system designed around the **Los Angeles market open**.
This strategy provides one highly filtered trade signal per day, helping you avoid noise and overtrading.
---
## ✅ Key Benefits
- 🔁 Only **one trade per day** – clean and focused approach
- ⏱ Optimized for **3-minute, 5-minute, and 15-minute** charts
- 🎯 Default **Take-Profit / Stop-Loss: 0.35%** (fully customizable)
- 🌎 Works on charts set to **Los Angeles timezone**
- 🧘 Ideal for **calm, structured, and part-time trading routines**
- 💼 Designed especially for **USDJPY** but may be applied to other high-volume FX pairs
---
## ⚙️ Settings Overview
- Opening Session Start Time (in LA time)
- Opening Range Duration (in minutes)
- Take-Profit and Stop-Loss percentages
- Force Close Time
- Trade Direction (Buy Only / Sell Only / Both)
---
## 💡 Who Is It For?
- Traders looking to simplify their day
- Those seeking **low-risk, steady profits**
- Anyone tired of chasing every move in the market
- FX traders who prefer **precision over frequency**
---
> 📌 **Note:** To ensure correct performance, set your TradingView chart’s timezone to **Los Angeles**.
---
### 🔵 Simple. Calm. Reliable.
The Multi Crossover Strategy [BoyaSignals]
📄 OVERVIEW
This strategy combines a layered entry system and adaptive risk management to capture opportunities across different market phases. Entries progress from deep reversals to momentum breakouts, using filters that adjust to trend, consolidation, or reversal conditions.
Advanced risk management features are built in, including a dynamic trailing stop and dynamic stop loss that adapt to volatility and trend conditions. These mechanisms are designed to help manage open positions more effectively than using fixed ATR multipliers alone.
The system includes enhanced backtesting statistics to help evaluate how changes in configuration affect historical performance. All backtesting results are for evaluation purposes only and should not be relied upon as an indicator of future performance.
For transparency, the strategy provides detailed chart labels showing the type of entry triggered, the entry filter number, real-time profit and loss percentages, and the reason for position closure. Display options allow users to show or hide labels and to overlay decision-related moving averages and Bollinger Bands for further context.
Alerts generated by this strategy can be used for discretionary entries or connected to automated trading platforms that accept TradingView webhook signals, such as Coinbase, Binance, and others. Some traders choose to integrate this setup with third-party services like Cryptohopper to automate execution, though this is entirely optional.
⸻
🔍 HOW DOES IT WORK
Signals are generated through a combination of momentum crossovers that pinpoint different stages of market movement. Each entry undergoes a series of checks across multiple indicators—including RSI, CCI, ADX, Bollinger Bands, moving averages, and volume—to confirm alignment with the strategy’s criteria.
Optional divergence detection across ten indicators can further strengthen signal quality and reduce the chance of false entries. In addition, global filters enforce conditions like minimum retracements, distance from key averages, and sufficient volatility before any trade is allowed.
Once an entry is active, stop losses and trailing stops adjust automatically in response to current volatility, momentum shifts, and recent price behavior. By sequencing filters and confirmations, the strategy aims to avoid chasing late moves while systematically identifying setups with the highest potential.
⸻
🎯 ENTRY TYPES
This strategy combines multiple entry methods to help identify potential opportunities across a variety of price conditions. Each entry type can be enabled or disabled individually and is evaluated using configurable filters and confirmation tools.
Stochastic RSI Crossover
Triggers when the Stochastic RSI K line crosses above the D line, often in oversold areas.
9-Period Moving Average Crossover
Triggers when price crosses the 9-period simple moving average.
MACD Crossover
Triggers when the MACD line crosses the signal line.
Big Bottom Entry
Designed to catch deep reversals before a Stochastic RSI crossover has formed.
Breakout Entry
Triggers when price exceeds recent high levels.
⸻
📊 MULTI-INDICATOR EVALUATION
Every entry signal is assessed using conditions including RSI, ADX, Stochastic, CCI, volume, volatility, price position relative to Bollinger Bands, proximity to the 50 and 200 moving averages, and additional proprietary filters. These filters help align entries with broader market context and avoid signals during unfavorable conditions.
⸻
🧭 DIVERGENCE CONFIRMATION
An additional confirmation layer can be added by checking for divergences around entry bar.
Settings let users customize how strict the divergence confirmation should be:
Specify the minimum number of divergences required
Allow divergence count overrides when volume is elevated
Require divergence on the crossover bar (stricter) or accept the nearest pivot (more flexible)
Enable divergence only when the market is not in an uptrend
Apply divergence checks selectively to specific entry types
Disable divergence validation entirely
⸻
🧩 ENTRY FILTERS
Filters Adapted To Price Context
Each entry method uses filters tailored to price conditions. For example, Stochastic RSI has distinct filters for downtrends, sideways moves, and retracements. 9MA and MACD entries check if price is above or below the basis line. You can enable or disable these filters to create stricter or more flexible entry criteria.
This is a layered approach that identifies opportunities progressively—from deep reversals to Stoch entries below the 9MA, then 9MA and MACD setups between averages and the upper Bollinger Band, and finally breakout entries at new highs. If one entry (e.g., a Stoch Crossover) doesn’t trigger, the strategy evaluates the next crossover filters as price rises.
Global Entry Filters
In addition to specific entry conditions, the strategy includes global filters to improve signal quality. These can:
Require a minimum distance above or below the 50 and 200 moving averages.
Define minimum and maximum retracement percentages in an uptrend.
Specify minimum distances from recent swing highs, swing lows, or resistance.
Set a minimum Bollinger Band width for entries.
Optionally disable entries entirely if the price is below key moving averages.
These filters can be adjusted or turned off to fine-tune selectivity.
⸻
🟢 DYNAMIC TRAILING STOPS
The strategy includes an advanced trailing stop mechanism that adapts to market conditions. Unlike a fixed ATR stop, this system evaluates multiple criteria to determine how aggressively or loosely to trail price.
The trailing stop becomes active only after price has reached a minimum profit level to avoid early tightening.
Dynamic ATR multipliers adjust between tight, narrow, and wide modes:
Wide trailing is used when strong bullish momentum, breakouts, or support above moving averages are detected.
Narrow trailing is applied during low volatility and early momentum loss.
Tight trailing activates if reversal signals appear, such as bearish divergences or trend exhaustion.
Evaluation factors include volatility, Bollinger Band compression, momentum slope and exhaustion patterns, price position relative to moving averages and bands, divergence signals, and recent swing levels.
You can define ATR multipliers, enable or disable tightening conditions, and choose adaptive or fixed trailing behavior.
Labels show when the trailing stop is armed and when adjustments occur.
Entry Label – In the snapshot above, you can see a Stoch Entry with the number 1 displayed below the “Stoch” label, indicating that Entry Filter 1 was the specific condition that triggered this trade.
Divergence Label – The entry was confirmed by divergences detected on four indicators at the entry bar: Stoch, CCI, CMF, and MFI. A green divergence label means regular divergences were found (hidden divergences are shown in orange).
Percentage Label – Where a position closes, you’ll see a percentage label showing the profit or loss achieved—green for profit, red for loss.
Trail Stop Label – The light blue label identifies which trailing stop rule closed the trade. In this snapshot, it was a tight stop loss triggered by bearish divergence.
Notice: A few bars to the left of this entry, there is another green divergence label without a corresponding entry signal. This indicates that although a divergence was detected, none of the entry filter criteria were met, so no trade was initiated.
⸻
🔴 DYNAMIC STOP LOSS
This strategy includes a comprehensive stop loss system that adapts as the market evolves. The stop loss can:
Use ATR-based or fixed percentage distance.
Tighten if early reversal risk appears , such as minor bearish movement or early trend shifts.
Tighten further if stronger bearish reversal signals confirm , including failed bounce attempts, rejection at resistance, or lower highs.
Define a maximum allowable loss per trade . By default, max stop loss is set to 3.5% below entry.
Allow a temporary extension beyond the max loss cap if bullish recovery signals appear, such as deep oversold conditions with momentum shift or successful bounces. By default, extended stop loss is enabled with 1.2% additional loss allowed.
Adjust to breakeven after reaching a defined profit.
Additional settings define how many bars must pass before certain stops activate, how long extended stops remain active, and what triggers a final exit. Labels show which stop type was triggered and why.
Examples to the use of extended SL:
A Reduced Loss Example:
A Reduced Loss Example 2:
Loss Turned Into Profit:
The “+” mark at the bottom of a bar indicates that the extended stop loss feature kept the position open due to detected reversal signals.
The “T” mark shows that the tight stop loss was triggered at that bar.
The red stop loss label above the closing bar displays the type of stop loss activated (e.g., Extended SL) and the reason for the exit (e.g., Breakdown).
⸻
STATISTICS AND BACKTESTING
The statistics provided in this strategy, help you analyze historical performance and see how changing the settings affects results .
Statistics include net profit, win rate, average win and loss size, maximum drawdown, risk/reward ratio, counts of each stop loss and trailing stop type, performance by entry method, filter-specific results, and monthly and yearly profit distributions.
The strategy was developed over the course of a full year, with extensive evaluation and testing on multiple coins and market conditions. By default all entry types and their related filters are activated. The default settings works well with many symbols but you will always need to fine-tune them in order to achieve best results for each symbol. Optimized results were found with DOGEUSDT on the 15 minute chart .
Although default settings can deliver strong performance on some symbols, it may produce poor results on others if left unadjusted. Tips for quickly tuning the configuration to different coins are provided at the end of this description.
⸻
ADDITIONAL LABELS
Skipped Divergence Labels
In the snapshot above, you can see an example of a label showing a skipped divergence. This means a divergence was detected on that bar but was not considered valid. A divergence will not be treated as valid if the number of divergences on that bar is less than the minimum defined in the settings, or if the type of divergence does not match the expected type for the current trend. Hidden divergences are used to confirm retracements during uptrends, while regular divergences are used to identify potential bottom reversals.
⸻
🧮 RISK ASSUMPTIONS AND DEFAULT SETTINGS
This strategy backtest uses a starting balance of $10,000 with 1 tick slippage and 0.075% commission. Position size defaults to 100% per trade to clearly measure the impact of each entry without partial allocations. The maximum stop loss is set at 3.5% below entry to limit downside risk, while an extended stop is activated by default (optional) and can widen losses by up to an additional 1.2%.
Why 100% Position Size is Used
This strategy defaults to allocating 100% of available equity per trade to simplify performance measurement and scaling. Because all entries are protected by defined stop loss levels (by default, maximum 3.5% of entry price + Extended stop loss % if activated), the actual risk per trade remains capped and does not exceed a sustainable portion of account equity. Users who prefer a different allocation can easily adjust position sizing in the Properties tab to match their preferred risk tolerance.
NOTICE & DISCLAIMER
This material is provided solely for personal study and demonstration. Redistribution, resale, modification, or any other use of these files or ideas is strictly prohibited. This tool does not provide financial advice or recommendations. Trading involves substantial risk and should be based on your own judgment. You are solely responsible for any decisions and outcomes.
No representation is made that the strategy will perform as intended in all situations. Automated systems may occasionally exit positions too early or too late, or extend trades when they should not. Use this information carefully and at your own discretion. No guarantees of performance or results are given.
⸻
TIPS FOR ADJUSTING SETTINGS TO VARIOUS SYMBOLS
There are a few simple steps I recommend when adapting the strategy to other coins or symbols:
1. Review the backtesting results.
Check whether there’s a healthy balance between wins and losses across most entry filters. If not, continue with the adjustments below.
2. Adjust divergence confirmation strictness.
For example, by default, Stoch Entries use the “Divergence / Uptrend” setting, requiring divergence only when an uptrend isn’t detected. Changing this to “After Divergence” forces every entry to confirm with divergence. Refer to the tooltips for each option to see how they impact signals.
3. Refine divergence settings.
Try adjusting the minimum number of divergences required to validate a signal and toggle the override divergence count switch. You can also experiment with enabling or disabling the other divergence-related toggles to see how they affect performance.
4. Deactivate specific entry filters.
If some filters still show a weak win/loss ratio after refining divergence criteria, consider turning them off to improve overall results.
5. Modify Narrow Trailing Stop behavior.
You can choose when the Narrow Trailing Stop should engage—either when bandwidth drops below 3% or when it falls under the average bandwidth of recent bars.
6. Adjust Global Entry Filters
Fine-tune the global filters to change thresholds for defining uptrends, retracements, minimum volatility, and conditions around key moving averages.
RSI Extreme Hit Tracker (Visual Enhanced + Stats)📊 Indicator Overview
🔥 RSI Extreme Hit Tracker – Visual Enhanced + Stats Edition
A high-precision momentum tracker designed for traders who want maximum insight into RSI behavior at extreme thresholds.
🧠 What It Tracks
This indicator doesn’t just alert you when RSI enters ultra-overbought or ultra-oversold zones—it actively logs, analyzes, and visualizes how price reacts during those periods.
It tracks:
- OB/OS HOLD Events: When RSI enters and stays in extreme zones for a customizable bar count
- OB/OS EXIT Events: When RSI retreats from extremes via hysteresis logic for adaptive confirmation
- Entry Alerts: Based on four modes (Basic, Cool-down, Confirmed, or Hysteresis)
- Tier Markers: Emoji-based tier tags to classify signal impact instantly on chart
- Background Tints: When OB/OS zones are active, for clear visual context
📈 Statistical Table
On every final bar, a clean table appears in the top-right corner showing:
- Count of OB/OS events (Hold & Exit)
- Total % move across all signals
- Average % move per signal
- Easy-to-skim P&L performance stats
🎛️ Configurable Features
🔄 Cool-down Periods: Prevent rapid-fire alerts after consecutive hits
🔍 Confirmed Entries: Require two-bar RSI zone confirmation before firing
🧪 Hysteresis Logic: Avoid false exits by confirming RSI decay before logging
📏 Custom Thresholds: Adjust OB/OS entry levels, exit hysteresis, and hold duration
🎨 Visual Feedback: Triangle, X-cross, and circle shapes with color-coded tier labels (🟩 🟨 🟦 🟥)
💡 Ideal Use Cases
- Reversal traders looking to time exhaustion and RSI flips
- Scalpers and momentum riders wanting sharp entry/exit maps
- Coders refining algorithms using historical signal behavior
- Analysts exploring data-driven signal statistics over time
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545Strategy Overview
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545 is a sophisticated breakout trading system designed for Bitcoin on the H1 timeframe. It integrates multiple volatility and price action indicators to identify high-probability breakout opportunities, aiming to capitalize on significant market movements.
Auther: @algochadlin
Strategy Logic
Breakout Confirmation: Utilizes a combination of Average True Range (ATR) and Bollinger Bands to identify periods of low volatility followed by sharp price movements.
Long: Initiated when the price breaks above the previous hour's upper Bollinger Band, with ATR confirming increased volatility.
Short: Triggered when the price breaks below the previous hour's lower Bollinger Band, with ATR indicating heightened volatility.
Parameters
Price Entry Multiplier: Adjusts the entry price relative to the breakout level.
Exit After Bars: Specifies the number of bars to hold the position before exiting.
Profit Target (%): Defines the percentage gain at which to take profit.
Stop Loss Coefficient: Multiplier for ATR to calculate stop-loss distance.
Trailing Stop Coefficients: Defines the trailing stop parameters.
Biggest Range Period: Determines the lookback period for identifying the largest price range.
Setup
Timeframe: 1-Hour (H1)
Asset: Bitcoin, also suitable for ETH
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Aftershock Playbook: Stock Earnings Drift EngineStrategy type
Event-driven post-earnings momentum engine (long/short) built for single-stock charts or ADRs that publish quarterly results.
What it does
Detects the exact earnings bar (request.earnings, lookahead_off).
Scores the surprise and launches a position on that candle’s close.
Tracks PnL: if the first leg closes green, the engine automatically re-enters on the very next bar, milking residual drift.
Blocks mid-cycle trades after a loss until the next earnings release—keeping the risk contained to one cycle.
Think of it as a sniper that fires on the earnings pop, reloads once if the shot lands, then goes silent until the next report.
Core signal inputs
Component Default Purpose
EPS Surprise % +0 % / –5 % Minimum positive / negative shock to trigger longs/shorts.
Reverse signals? Off Quick flip for mean-reversion experiments.
Time Risk Mgt. Off Optional hard exit after 45 calendar days (auto-scaled to any TF).
Risk engine
ATR-based stop (ATR × 2 by default, editable).
Bar time stop (15-min → Daily: Have to select the bar value ).
No pyramiding beyond the built-in “double-tap”.
All positions sized as % of equity via Strategy Properties.
Visual aids
Yellow triangle marks the earnings bar.
Diagnostics table (top-right) shows last Actual, Estimate, and Surprise %.
Status-line tool-tips on every input.
Default inputs
Setting Value
Positive surprise ≥ 0 %
Negative surprise ≤ –5 %
ATR stop × 2
ATR length 50
Hold horizon 350 ( 1h timeframe chart bars)
Back-test properties
Initial capital 10 000
Order size 5 % of equity
Pyramiding 1 (internal re-entry only)
Commission 0.03 %
Slippage 5 ticks
Fills Bar magnifier ✔ · On bar close ✔ · Standard OHLC ✔
How to use
Add the script to any earnings-driven stock (AAPL, MSFT, TSLA…).
Turn on Time Risk Management if you want stricter risk management
Back-test different ATR multipliers to fit the stock’s volatility.
Sync commission & slippage with your broker before forward-testing.
Important notes
Works on every timeframe from 15 min to 1 D. Sweet spot around 30min/1h
All request.earnings() & request.security() calls use lookahead_off—zero repaint.
The “double-tap” re-entry occurs once per winning cycle to avoid drift-chasing loops.
Historical stats ≠ future performance. Size positions responsibly.
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them.
It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes.
I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that.
Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should).
I have my own ideas of improvements which I will probably implement separately to keep this clean.
Double Bottom Strategy (Long Only, ATR Trailing Stop + Alerts)This script implements a long-only breakout strategy based on the recognition of a Double Bottom price pattern, enhanced with a 50 EMA trend filter and a dynamic ATR-based trailing stop. It is suitable for traders looking to capture reversals in trending markets using a structured pattern-based entry system.
🧠 Key Features:
Double Bottom Detection: Identifies double bottom structures using pivot lows with configurable tolerance.
ATR-Based Trailing Stop: Manages exits using a trailing stop calculated from Average True Range (ATR), dynamically adjusting to market volatility.
EMA Filter (Optional): Filters trades to only go long when price is above the 50 EMA (trend confirmation).
Alerts: Real-time alerts on entry and exit, formatted in JSON for webhook compatibility.
Backtest Range Controls: Customize historical testing period with start and end dates.
✅ Recommended Markets:
Gold (XAUUSD)
S&P 500 (SPX, ES)
Nasdaq (NDX, NQ)
Stocks (Equities)
⚠️ Not recommended for Forex due to differing behavior and noise levels in currency markets.
🛠️ User Guidance:
Tune the pivot period, tolerance, and ATR settings for best performance on your chosen asset.
Backtest thoroughly over your selected date range to assess historical effectiveness.
Use small position sizes initially to test viability in live or simulated environments.
PRO Trading Averaging Beta(v1)Adaptive Position Scaling
Automatically increases position size during pullbacks using exponential volume scaling (1x, 2x, 4x, etc.). This reduces average entry cost and accelerates breakeven when price reverses.
Multi-Timeframe Confirmation
All indicators operate on a higher timeframe (120 minutes), providing:
Noise-filtered signals
Stronger trend alignment
Reduced false entries
Triple-Layer Entry Logic
Requires simultaneous confluence of:
Custom Bollinger Band penetration
RSI oversold filter (above critical threshold)
Golden cross confirmation (fast MA > slow MA)
Volatility assessment via ATR
Intelligent Exit System
Position closure triggers when either:
Fixed profit target (% of account) is reached
Technical boundary (upper Bollinger Band) is touched
⚙️ Core Mechanics:
graph LR
A --> B
B --> C{Initial Entry: 1% capital}
C --> D
D -->|Yes| E
D -->|No| F
E --> G{Max Averaging Levels?}
G -->|No| D
G -->|Yes| H
F --> I
📊 Implementation Guide:
Capital Configuration
Set initial_capital to your actual account size
Calculate base contract size:
(Account Size × 0.01) / (Instrument Price × Point Value)
Example: $10,000 account → 0.01 BTC futures contracts
Pyramiding Structure
Volume progression per averaging level:
Level 1: 1× (Base volume)
Level 2: 2×
Level 3: 4×
Level 4: 8×
Level 5: 16×
Level 6: 32×
(Max 6 levels configurable in strategy settings)
Custom Entry Variations
Alternative approach for swing captures:
// Enter only at 3rd averaging with 5% capital
if averaging_condition and strategy.opentrades == 2
strategy.entry("SwingEntry", strategy.long, qty=base_order_size*5)
Risk Management Protocol
No traditional stop-loss (replaced by averaging)
Break-even trigger: Manually move to breakeven at +0.5% profit
Max exposure: Capped at 6 averaging levels
Commissions: Pre-configured at 0.1% per trade
⚠️ Critical Risk Disclosures:
"Past Performance ≠ Future Results"
Historical optimization requires continuous forward testing ("Walk Forward" in TV).
Pyramiding Hazards
Exponential volume growth demands:
Minimum 20% free margin buffer
High liquidity instruments (spread < 0.5% of ATR)
Strict per-level risk calculation
Market Regime Dependence
Peak efficiency during:
Strong trends with 2-4% retracements
Assets with ATR > 1.5% of daily range
Avoid ranging/low-volatility conditions
💡 Pro Usage Recommendations:
Position Sizing Formula
For futures: Contracts = (Capital × Risk %) / (Entry Price × Point Value × Stop Distance)
Profit Protection
Close 50% position at 50% profit target, trail remainder
Event Safety
Disable averaging during:
High-impact news events
Exchange outages
Abnormal volume spikes
pie
title Risk Allocation per Level
“First Entry” : 12
“Level 2” : 18
“Level 3” : 25
“Level 4” : 45
ESSENTIAL: This strategy demands strict discipline. Terminate averaging when price action deviates from expected patterns. Always maintain reserve capital exceeding maximum drawdown requirements. Regularly validate strategy performance against current market dynamics.
🔥 Уникальные особенности и ценность:
Адаптивное усреднение
Стратегия автоматически увеличивает позицию при движении против вас, используя экспоненциальное наращивание объема (1x, 2x, 4x и т.д.). Это снижает среднюю цену входа и ускоряет выход в прибыль при развороте.
Мультитаймфреймная фильтрация
Все индикаторы работают на старшем таймфрейме (120 минут), что:
Фильтрует рыночный шум
Обеспечивает более надежные сигналы
Синхронизируется с глобальным трендом
Комбинированный триггер входа
Для активации требуется одновременное выполнение 4 условий:
Пробитие кастомной полосы Боллинджера
Подтверждение тренда (быстрая MA > медленной MA)
Контроль перепроданности (RSI выше критического уровня)
Фильтр волатильности (ATR)
Двойной механизм выхода
Закрытие позиций происходит при:
Достижении целевого уровня прибыли (% от депозита)
Техническом сигнале (касание верхней полосы Боллинджера)
⚙️ Как работает стратегия:
graph TD
A --> B
B --> C{Первый вход: 1% депозита}
C --> D
D -->|Да| E
D -->|Нет| F
E --> G{Достигнут лимит усреднений?}
G -->|Нет| D
G -->|Да| H
F --> I
📊 Как пользоваться:
Стартовые настройки
Base Order Size: Стартовый объем = 1% депозита
(Пример: при $10 000 депозита = 0.01 контракта)
initial_capital: Укажите ваш реальный депозит
Правила пирамидинга
Объем наращивается по схеме:
Уровень 1: 1x (базовый объем)
Уровень 2: 2x
Уровень 3: 4x
Уровень 4: 8x
Уровень 5: 16x
Уровень 6: 32x
РЕКОМЕНДУЕТСЯ Максимум 6 уровней усреднения (настраивается в pyramiding)
Кастомизация входов
Пример модификации для агрессивной тактики:
// Вход только на 3-м усреднении с 5% депозита
if averaging_condition and strategy.opentrades == 2
strategy.entry("BuyAggressive", strategy.long, qty=base_order_size*5)
Можно поставить параметр пираммидинг 1 и получать больше сигналов на младших тайм фреймах
Управление рисками
Стоп-лосс: Не используется (заменен усреднением)
Перевод в безубыток: Активируйте вручную при +0.5%
Максимальная просадка: Рекомендуется Ограничивать 6 уровнями усреднения
Комиссии: Учтены (0.1% от объема сделки)
Критические предупреждения:
"Вчера ≠ Сегодня"
Стратегия оптимизирована под историческую волатильность. Регулярно тестируйте на новых данных (режим "Перед тест" в TV).
Опасность усреднения
Экспоненциальный рост объема требует:
Глубокого расчета риска на уровень
Минимум 20% свободного маржи
Ликвидный инструмент (спред < 0.5% от ATR)
Рыночные условия
Максимальная эффективность в:
Трендовых рынках с коррекциями 2-4%
Инструментах с ATR > дневного диапазона 1.5%
💡 Рекомендации по использованию:
Для фьючерсов: Рассчитайте контракты через (капитал * 0.01) / (цена * пункт_стоимости)
При 50% достижении цели прибыли - закройте 50% позиции
Отключайте усреднение при выходе макро-новостей
pie
title Распределение риска
"Первый вход" : 10
"Уровень 2" : 20
"Уровень 3" : 30
"Уровень 4" : 40
ВАЖНО: Эта стратегия требует дисциплины! Прекращайте усреднение при отклонении рынка от исторических паттернов. Всегда имейте резервный капитал для экстренных случаев.
Price Statistical Strategy-Z Score V 1.01
Price Statistical Strategy – Z Score V 1.01
Overview
A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”.
This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included.
Core Methodology
The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits.
Signal Conditions
Entry Condition:
A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met.
Exit Condition:
The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow.
Signal Gapping:
A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise.
Momentum Filter:
Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles.
Z-Score Function
The Z-Score is calculated as:
Z = (Close - SMA(Close, N)) / STDEV(Close, N)
Where N is the base period selected by the user.
Input Parameters
Enable Smoothed Z-Score Strategy
Enables or disables the Z-Score strategy logic. When disabled, no trades are executed.
Z-Score Base Period
Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes.
Short-Term Smoothing
Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility.
Long-Term Smoothing
Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic.
Bars gap between identical signals
Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals.
Trade Visualization Table
A table positioned at the bottom-right displays live PnL for open trades:
Entry Price
Unrealized PnL %
Text colors adapt based on whether unrealized profit is positive, negative, or neutral.
Technical Notes
This strategy uses only close prices — no trend indicators or volume components are applied.
All calculations are based on simple moving averages and standard deviation over user-defined windows.
Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
QQQ Strategy v2 ESL | easy-peasy-x This is a strategy optimized for QQQ (and SPY) for the 1H timeframe. It significantly outperforms passive buy-and-hold approach. With settings adjustments, it can be used on various assets like stocks and cryptos and various timeframes, although the default out of the box settings favor QQQ 1H.
The strategy uses various triggers to take both long and short trades. These can be adjusted in settings. If you try a different asset, see what combination of triggers works best for you.
Some of the triggers employ LuxAlgo's Ultimate RSI - shoutout to him for great script, check it out here .
Other triggers are based on custom signed standard deviation - basically the idea is to trade Bollinger Bands expansions (long to the upside, short to the downside) and fade or stay out of contractions.
There are three key moving averages in the strategy - LONG MA, SHORT MA, BASIC MA. Long and Short MAs are guides to eyes on the chart and also act as possible trend filters (adjustable in settings). Basic MA acts as guide to eye and a possible trade trigger (adjustable in settings).
There are a few trend filters the strategy can use - moving average, signed standard deviation, ultimate RSI or none. The filters act as an additional condition on triggers, making the strategy take trades only if both triggers and trend filter allows. That way one can filter out trades with unfavorable risk/reward (for instance, don't long if price is under the MA200). Different trade filters can be used for long and short trades.
The strategy employs various stop loss types, the default of which is a trailing %-based stop loss type. ATR-based stop loss is also available. The default 1.5% trailing stop loss is suitable for leveraged trading.
Lastly, the strategy can trigger take profit orders if certain conditions are met, adjustable in settings. Also, it can hold onto winning trades and exit only after stop out (in which case, consecutive triggers to take other positions will be ignored until stop out).
Let me know if you like it and if you use it, what kind of tweaks would you like to see.
With kind regards,
easy-peasy-x
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
Cyber Strategy V1Сyber Strategy V1 – Indicator Testing & Strategy Execution Framework
✅ Overview
Cyber Strategy V1 is a closed-source strategy framework engineered to turn any of yours external indicator into a systematic, rule-based trading system. Designed for rigorous testing and live deployment, it combines multi-signal inputs, confirmations and automated execution paths to help traders and developers validate signal quality and manage risk with precision.
✅ Core Functionality
Multi-Source Independent Signal Inputs
Reversal Logic
Take Profit: up to 5 staggered TP levels, specified as percentage
Stop Loss: configurable via fixed percentage or dynamic SL that trails a reverse signals.
✅ Statistical Drawdown Analysis
For all profitable trades, tracks the maximum intratrade drawdown.
Computes percentile levels of profitable trades that hits minimum drawdowns to inform:
Entry buffer zones (e.g. avoid entering during transient noise)
Partial entry scaling prices.
✅ Signal Confirmation
Optional confirmation delays: hold entry until other signal section send a confirmation from another indicator.
✅ Automated Execution Integrations
Cornix Text Alerts: Generates pre-formatted alerts compatible with Cornix for semi-automated or bot trading.
Webhook Support: Emits JSON payloads on order-fill events to any endpoint, enabling full automation through third-party services or custom order-routing systems.
Important Notes
⚠️ THIS STRATEGY DOES NOT INCLUDE INDICATORS. Examples shown on screenshots use third-party tools. NO PROPRIETARY INDICATORS INCLUDED: Cyber Strategy V1 relies entirely on external signal inputs.
⚠️ All backtesting parameters are customizable; thorough backtesting under realistic slippage, fees and spread assumptions is essential before live deployment.
AltCoin Index Correlation🧠 AltCoin Index Correlation — Strategy Overview
AltCoin Index Correlation is a dynamic EMA-based trading strategy designed primarily for altcoins, but also adaptable to stocks and indices, thanks to its flexible reference index system.
🧭 Strategy Philosophy
The core idea behind this strategy is simple yet powerful:
Price action becomes more meaningful when it aligns with broader market context.
This script analyzes the correlation between the asset’s trend and a reference index trend, using dual EMA (Exponential Moving Average) crossovers for both.
When both the altcoin and the reference index (e.g. Altcoin Dominance, BTC Dominance, Total Market Cap, or even indices like the NASDAQ 100 or S&P 500) are aligned in trend direction, the script considers it a high-confidence setup.
It also includes:
Optional inverse correlation logic (for contrarian setups)
Custom leverage settings (e.g., 1x, 1.8x, etc.)
A dynamic scale-out mechanism during weakening trends
Date filtering for controlled backtests
A live performance dashboard with equity, PnL, win rate, drawdown, APR, and more
⚙️ Default Settings & Backtest Results
Timeframe tested: 1H
Test date: May 20, 2025
Sample: 100 high-cap altcoins
Reference index: CRYPTOCAP:OTHERS.D (Altcoin Dominance)
Leverage: 1.8x (180% of capital used)
📊 With default settings:
Win rate: ~80%
Higher profits, due to increased exposure
Best suited for confident trend followers with higher risk tolerance
📉 With fixed capital or 1x leverage:
Win rate improves to ~90%
Lower returns, but greater capital preservation
Ideal for conservative or risk-managed trading styles
🔄 Versatility
While tailored for altcoins, this strategy supports traditional markets as well:
Easily switch the reference index to OANDA:NAS100USD or S&P 500 for stock correlation trading
Adjust EMA lengths and leverage to match the asset class and volatility profile
🧩 Suggested Use
Best used on trending markets (not sideways)
Ideal for 1H timeframes, but adjustable
Suitable for traders who want a rules-based, macro-aware entry/exit system
Try it out, customize it to your style, try different settings and share your results with the community!
Feedback is welcome — and improvements are always in progress.
🚀 ### Check my profile for other juicy hints and original strategies. ### 🚀
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
