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. ### 🚀
Moving Averages
Livermore-Seykota Breakout StrategyStrategy Name: Livermore-Seykota Breakout Strategy
Objective: Execute breakout trades inspired by Jesse Livermore, filtered by trend confirmation (Ed Seykota) and risk-managed with ATR (Paul Tudor Jones style).
Entry Conditions:
Long Entry:
Close price breaks above recent pivot high.
Price is above main EMA (EMA50).
EMA20 > EMA200 (uptrend confirmation).
Current volume > 20-period SMA (volume confirmation).
Short Entry:
Close price breaks below recent pivot low.
Price is below main EMA (EMA50).
EMA20 < EMA200 (downtrend confirmation).
Current volume > 20-period SMA.
Exit Conditions:
Stop-loss: ATR × 3 from entry price.
Trailing stop: activated with offset of ATR × 2.
Strengths:
Trend-aligned entries with volume breakout confirmation.
Dynamic ATR-based risk management.
Inspired by principles of three legendary traders.
Scalping EMA + RSI Strategy (Long & Short)Scalping EMA with RSI Strategy.
Entry Criteria: Indicators, price action, or patterns triggering entries.
Stop Loss (SL): Fixed pips, ATR-based, or swing low/high.
Take Profit (TP): Fixed reward, trailing stop, or dynamic levels.
RRR Target: e.g., 1:1.5 or 1:2.
SMA + Range Breakout StrategySimple Moving Average with Range Breakout with RSI confirmation having Trailing Stop Loss
Trailing Stop-Loss
RSI Confirmation Filter
Breakout Alerts
8/21 EMA Crossover + VWAP + 200 EMA8/21 EMA crossover with VWAP and slow moving average confirmation
My Strategy fo CashNot sure how it works but works excellent on NQ Futures on a 9 minute chart. Im still trying to automate. No experience there. Todays its 5/20/25 and the profit was 5k with only using 1 contract at a time. drawdown was 1500 or .1%. If you have any thoughts on automating please let me know. ill start researching t now, because with back testing it was profitable for the last 3 years. Thanks!
CANX MA Crossover© CanxStixTrader
Moving average crossover systems measure drift in the market. They are great strategies for time-limited traders. KEEP IT SIMPLE
This strategy works both for buys and sells using the reaction line to guide your position against the reactions.
HOW TO USE THE INDICATOR
1) Choose your market and timeframe.
2) Choose the length.
3) Choose the multiplier.
4) Choose if the strategy is long-only or bidirectional (longs & shorts).
TIPS
The strategy works best in bullish markets as that is the primary direction that market such as stocks, indexes and metals like to move.
- Increase the multiplier to reduce whipsaws
- Increase the length to take fewer trades
- Decrease the length to take more trades
- Try a Long-Only strategy to see if that performs better.
The base set up when you load the indicator is for the 1 minute chart on gold. We found that it also works well on the US Indexes. For other markets you may need to change the length and multiplier to suit the market and back test its results.
Backtest: EMA + CPR + Volume + SL/TargetBacktest Strategy — EMA + CPR + Volume + SL/Target
Buy & Sell signals: Plotted on chart
Volume Spike Filter: Volume > 20-day average
Stop-Loss: 1.5% below entry price
Target: 3% above entry price (can be adjusted)
Backtest mode: Tracks performance
Works on all stocks (Futures or Equity)
EMA 10/20/50 Alignment Strategy### 📘 **Strategy Name**
**EMA 10/20/50 Trend Alignment Strategy**
---
### 📝 **Description (for Publishing)**
This strategy uses the alignment of Exponential Moving Averages (EMAs) to identify strong bullish trends. It enters a long position when the short-term EMA is above the mid-term EMA, which is above the long-term EMA — a classic sign of trend strength.
#### 🔹 Entry Criteria:
* **EMA10 > EMA20 > EMA50**: A bullish alignment that signals momentum in an upward direction.
* The strategy enters a **long position** when this alignment occurs.
#### 🔹 Exit Criteria:
* The long position is closed when the EMA alignment breaks (i.e., the trend weakens or reverses).
#### 🔹 Additional Features:
* Includes a **date range filter**, allowing you to backtest the strategy over a specific period.
* Uses **100% of available capital** for each trade (position size auto-scales with account balance).
* No short positions, stop loss, or take profit are applied — this is a trend-following strategy meant to ride bullish moves.
---
### ✅ Best For:
* Traders looking for a **simple, trend-based entry system**
* Testing price momentum strategies during specific market regimes
* Visualizing EMA stacking patterns in historical data
Backtest with Date Range### 📝 Strategy Description for Publishing
**Title**: SMA Crossover Strategy with Custom Date Range
**Description**:
This strategy implements a classic SMA (Simple Moving Average) crossover system, enhanced with a custom backtesting window defined by start and end dates.
It generates:
* **Buy signals** when the 10-period SMA crosses above the 50-period SMA (bullish momentum).
* **Sell signals** when the 10-period SMA crosses below the 50-period SMA (bearish momentum).
Key features:
* Trades only occur within a user-defined date range, allowing precise control over the backtest period.
* Uses 100% of available capital per trade by default.
* No leverage or stop loss/take profit is applied—pure trend-following logic.
Ideal for users looking to validate moving average-based strategies during specific market conditions or events.
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.
RSI-SMA + ADX + EMA Optimized StrategyRSI-SMA Crossover Strategy for Nifty Option Buying
Strategy Type: Intraday or Swing
Instruments: Nifty ATM Options (Weekly expiry)
Chart Timeframe: 5-minute (for intraday) or 15-minute (for short-term trades)
Indicators Used:
RSI (Relative Strength Index) – 14 period
SMA (Simple Moving Average) of RSI – typically 9 or 10 period
Entry Rules:
Buy ATM Call Option (Bullish Setup):
RSI crosses above its SMA (RSI line crosses above RSI-SMA).
RSI is above 50 at the time of crossover.
Nifty price is above 20 EMA (optional filter for trend confirmation).
Buy ATM Call Option of current week expiry.
Buy ATM Put Option (Bearish Setup):
RSI crosses below its SMA.
RSI is below 50 at the time of crossover.
Nifty price is below 20 EMA (optional).
Buy ATM Put Option of current week expiry.
Exit Rules:
Target: 30–50% profit on premium
Stop-loss: 25–30% of premium OR opposite crossover
Time-based exit: Square off by 3:15 PM (for intraday)
Сига EMA-RSIConditions
- The signal is formed only when the EMA9 and EMA20 intersect and the RSI conditions are met
The precondition is that the RSI should break through the 55 level from top to bottom for long and 45 from bottom to top for short
- The signal is formed when EMA9 and EMA20 intersect and the RSI condition is met
This combination works perfectly on trend reversals.Patterns.
Сига EMA-RSIConditions
- The signal is formed only when the EMA9 and EMA20 intersect and the RSI conditions are met
The precondition is that the RSI should break through the 55 level from top to bottom for long and 45 from bottom to top for short
- The signal is formed when EMA9 and EMA20 intersect and the RSI condition is met
This combination works perfectly on trend reversals.Patterns.
Quant Trading Zero Lag Trend Signals (MTF) StrategyMy own zero lag indicator building on top of algo alpha, but includes
several dynamic exits including
exit with risk/reward,
exist with profit target,
ATR Based Stop Loss & Take Profit,
Profit Target ATR Multiplier
Trailing Stop Loss
Break Even Stop Loss
EMA Exit.
Also added features to long or long and short.
Added Re-Entry on Zero Line (ZLEMA).
Works well, especially with higher lengths and higher timeframes.
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
HMA 200 + EMA 20 Crossover StrategyThis strategy combines a long-term trend filter using the Hull Moving Average (HMA 200) with a short-term entry trigger using the Exponential Moving Average (EMA 20).
📈 Entry Logic:
Buy Entry: When price is above the HMA 200 and crosses above the EMA 20.
Sell Entry: When price is below the HMA 200 and crosses below the EMA 20.
The strategy closes the current position and reverses on the opposite signal.
⚙️ Strategy Settings (Backtest Configuration):
Position size: 10% of equity per trade
Commission: 0.1% per trade (to simulate broker fees)
Slippage: 2 ticks (to reflect realistic fill conditions)
✅ Purpose:
This script is designed to identify high-probability trades in the direction of the overall trend, avoiding whipsaw conditions. It is useful for traders looking for a dynamic crossover-based system that filters trades based on longer-term momentum.
🔎 Make sure to test across multiple assets and timeframes. For best results, apply this strategy to liquid trending markets like major FX pairs, indices, or high-cap stocks.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
SMPivot Gaussian Trend Strategy [Js.K]This open-source strategy combines a Gaussian-weighted moving average with “Smart Money” swing-pivot breaks (BoS = Break-of-Structure) to capture trend continuations and early reversals. It is intended for educational and research purposes only and must not be interpreted as financial advice.
How the logic works
-------------------
1. Gaussian Moving Average (GMA)
• A custom Gaussian kernel (length = 30 by default) smooths price while preserving turning points.
• A second pass (“Smoothed GMA”) further filters noise; only its direction is used for bias.
2. Swing-Pivot detection
• High/Low pivots are found with a symmetric look-back/forward window (Pivot Length = 20).
• The most recent confirmed pivot creates a dynamic structure level (UpdatedHigh / UpdatedLow).
3. Entry rules
Long
• Price closes above the most recent pivot high **and** above Smoothed GMA.
Short
• Price closes below the most recent pivot low **and** below Smoothed GMA.
4. Exit rules
• Fixed stop-loss and take-profit in percent of current price (user-defined).
• Separate parameters and on/off switches for longs and shorts.
5. Visuals
• GMA (dots) and Smoothed GMA (line).
• Structure break lines plus “BoS PH/PL” labels at the midpoint between pivot and break.
Inputs
------
Gaussian
• Gaussian Length (default 30) – smoothing window.
• Gaussian Scatterplot – toggle GMA dots.
Smart-Money Pivot
• Pivot Length (default 20).
• Bull / Bear colors.
Risk settings
• Long / Short enable.
• Individual SL % and TP % (default 1 % SL, 30 % TP).
• Strategy uses percent-of-equity sizing; initial capital defaults to 10 000 USD.
Adjust these to reflect your own account size, realistic commission and slippage.
Best practice & compliance notes
--------------------------------
• Test on a data sample that yields ≥ 100 trades to obtain statistically relevant results.
• Keep risk per trade below 5–10 % of equity; the default values comply with this guideline.
• Explain any custom settings you publish that differ from the defaults.
• Do **not** remove the code header or licence notice (MPL-2.0).
• Include realistic commission and slippage in your back-test before publishing.
• The script does **not** repaint; orders are processed on bar close.
Usage
-----
1. Add the script to any symbol / timeframe; intraday and swing timeframes both work—adjust lengths accordingly.
2. Configure SL/TP and position size to match your personal risk management.
3. Run “List of trades” and the performance summary to evaluate expectancy; forward-test before live use.
Disclaimer
----------
Trading involves substantial risk. Past performance based on back-testing is not necessarily indicative of future results. The author is **not** responsible for any financial losses arising from the use of this script.
Triangle Breakout Strategy with TP/SL, EMA Filter📌 Triangle Breakout Strategy with TP/SL, EMA Filters, and Backtest – Explained.
✅ 1. Pattern Detection – Triangle Breakout
The script scans for triangle patterns by detecting local pivot highs and pivot lows.
It uses two recent highs and two recent lows to draw converging trendlines (upper and lower boundaries of the triangle).
If the price breaks above the upper trendline, a bullish breakout signal is generated.
🎯 2. TP (Take Profit) & SL (Stop Loss)
When a bullish breakout is detected:
A buy order is placed using strategy.entry.
TP and SL levels are calculated relative to the current close price:
TP = 3% above the entry price
SL = 1.5% below the entry price
These are defined using strategy.exit.
📊 3. EMA Filter
An optional filter checks if:
Price is above both EMA 20 and EMA 50
Only if this condition is met, the strategy allows a long entry.
You can toggle the filter on or off with useEMAFilter.
📈 4. Backtesting with Strategy Tester
This script uses strategy() instead of indicator() to enable TradingView’s built-in backtest engine.
Every buy entry and exit (based on TP or SL) is recorded.
📌 5. Visuals
EMA 20 and EMA 50 lines are plotted on the chart.
A label is shown when a breakout is detected: "Breakout Up"
Results (profit, win rate, drawdown, etc.) can be viewed in the Strategy Tester panel.
Fibonacci + TP/SL Strategy [Backtest]✅ Key Features Added and Adjusted:
Fibonacci Retracement Levels:
Automatically calculated based on the last 100 bars' high/low
Plotted levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
Extension targets: 161.8%, 261.8%, 423.6%
Buy/Sell Signal Logic:
Buy: Price is between 78.6% and 38.2% levels
Sell: Price is between 61.8% and 23.6% levels
Both depend on a can_trade time filter to avoid overtrading
ATR-based Stop-Loss:
Stop-loss dynamically adapts to market volatility:
SL = Entry - ATR * 1.5 (long)
SL = Entry + ATR * 1.5 (short)
Fixed Take-Profit:
Configurable via input: default is 4%
Can be changed in TradingView UI
Golden/Death Cross Indicator (Visual Only):
EMA 50 crossing EMA 200 plotted on chart:
Golden Cross = Buy signal (green triangle)
Death Cross = Sell signal (red triangle)
Weekly Profit Cap:
Prevents new trades if weekly profit exceeds 15%
Resets at the start of every week
Visual Elements:
All Fibonacci levels are plotted
Buy/Sell signals are labeled on the chart (BUY, SELL)
30-70 RSI Strategy with Colored BarThis script colors price bars based on Relative Strength Index (RSI) levels, giving traders a quick and visual way to assess overbought or oversold market conditions directly on the chart.
📈 Key Features:
✅ RSI-Based Bar Coloring:
Green bars when RSI is above the upper threshold (default 70) – suggests bullish momentum.
Red bars when RSI is below the lower threshold (default 30) – indicates bearish pressure.
Bars remain uncolored when RSI is between thresholds – a neutral zone.
🔧 Customizable RSI Settings:
Adjustable RSI length (default: 14 periods)
Adjustable overbought/oversold levels (default: 70/30)
🧠 Helps traders:
Quickly spot potential reversals or trend continuations
Visually align price action with momentum
🛠️ Usage:
Ideal for trend-following, reversal, and momentum strategies.
Works across any timeframe (1m, 5m, 1h, daily, etc.).