EMA Crossover Strategy with Trailing Stop and AlertsPowerful EMA Crossover Strategy with Dynamic Trailing Stop and Real-Time Alerts
This strategy combines the simplicity and effectiveness of EMA crossovers with a dynamic trailing stop-loss mechanism for robust risk management.
**Key Features:**
* **EMA Crossover Signals:** Identifies potential trend changes using customizable short and long period Exponential Moving Averages.
* **Trailing Stop-Loss:** Automatically adjusts the stop-loss level as the price moves favorably, helping to protect profits and limit downside risk. The trailing stop percentage is fully adjustable.
* **Visual Buy/Sell Signals:** Clear buy (green upward label) and sell (red downward label) signals are plotted directly on the price chart.
* **Customizable Inputs:** Easily adjust the lengths of the short and long EMAs, as well as the trailing stop percentage, to optimize the strategy for different assets and timeframes.
* **Real-Time Alerts:** Receive instant alerts for buy and sell signals, ensuring you don't miss potential trading opportunities.
**How to Use:**
1. Add the strategy to your TradingView chart.
2. Customize the "Short EMA Length," "Long EMA Length," and "Trailing Stop Percentage" in the strategy's settings.
3. Enable alerts in TradingView to receive notifications when buy or sell signals are generated.
This strategy is intended to provide automated trading signals based on EMA crossovers with built-in risk management. Remember to backtest thoroughly on your chosen instruments and timeframes before using it for live trading.
#EMA
#Crossover
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PVT Crossover Strategy**Release Notes**
**Strategy Name**: PVT Crossover Strategy
**Purpose**: This strategy aims to capture entry and exit points in the market using the Price-Volume Trend (PVT) and its Exponential Moving Average (EMA). It specifically uses the crossover of PVT with its EMA as signals to identify changes in market trends.
**Uniqueness and Usefulness**
**Uniqueness**: This strategy is unique in its use of the PVT indicator, which combines price changes with trading volume to track trends. The filtering with EMA reduces noise and provides more accurate signals compared to other indicators.
**Usefulness**: This strategy is effective for traders looking to detect trend changes early. The signals based on PVT and its EMA crossover work particularly well in markets where volume fluctuations are significant.
**Entry Conditions**
**Long Entry**:
- **Condition**: A crossover occurs where PVT crosses above its EMA.
- **Signal**: A buy signal is generated, indicating a potential uptrend.
**Short Entry**:
- **Condition**: A crossunder occurs where PVT crosses below its EMA.
- **Signal**: A sell signal is generated, indicating a potential downtrend.
**Exit Conditions**
**Exit Strategy**:
- The strategy does not explicitly program exit conditions beyond the entry signals, but traders are encouraged to close positions manually based on signals or apply their own risk management strategy.
**Risk Management**
This strategy does not include default risk management rules, so traders should implement their own. Consider using trailing stops or fixed stop losses to manage risk.
**Account Size**: ¥100,000
**Commissions and Slippage**: 94 pips per trade for commissions and 1 pip for slippage
**Risk per Trade**: 10% of account equity
**Configurable Options**
**Configurable Options**:
- **EMA Length**: The length of the EMA used to calculate the EMA of PVT (default is 20).
- **Signal Display Control**: The option to turn the display of signals on or off.
**Adequate Sample Size**
To ensure the robustness and reliability of this strategy, it is recommended to backtest it with a sufficiently long period of historical data, especially across different market conditions.
**Credits**
**Acknowledgments**:
This strategy is based on the concept of the PVT indicator and its application in strategy design, drawing on contributions from technical analysis and the trading community.
**Clean Chart Description**
**Chart Appearance**:
This strategy is designed to maintain a clean and simple chart by turning off the plot of PVT, its EMA, and entry signals. This reduces clutter and allows for more effective trend analysis.
**Addressing the House Rule Violations**
**Omissions and Unrealistic Claims**
**Clarification**:
This strategy does not make unrealistic or unsupported claims about its performance, and all signals are for educational purposes only, not guaranteeing future results. It is important to understand that past performance does not guarantee future outcomes.
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
EDMA Scalping Strategy (Exponentially Deviating Moving Average)This strategy uses crossover of Exponentially Deviating Moving Average (MZ EDMA ) along with Exponential Moving Average for trades entry/exits. Exponentially Deviating Moving Average (MZ EDMA ) is derived from Exponential Moving Average to predict better exit in top reversal case.
EDMA Philosophy
EDMA is calculated in following steps:
In first step, Exponentially expanding moving line is calculated with same code as of EMA but with different smoothness (1 instead of 2).
In 2nd step, Exponentially contracting moving line is calculated using 1st calculated line as source input and also using same code as of EMA but with different smoothness (1 instead of 2).
In 3rd step, Hull Moving Average with 2/3 of EDMA length is calculated using final line as source input. This final HMA will be equal to Exponentially Deviating Moving Average.
EDMA Defaults
Currently default EDMA and EMA length is set to 20 period which I've found better for higher timeframes but this can be adjusted according to user's timeframe. I would soon add Multi Timeframe option in script too. Chikou filter's period is set to 25.
Additional Features
EMA Band: EMA band is shown on chart to better visualize EMA cross with EDMA .
Dynamic Coloring: Chikou Filter library is used for derivation of dynamic coloring of EDMA and its band.
Trade Confirmation with Chikou Filter: Trend filteration from Chikou filter library is used as an option to enhance trades signals accuracy.
Strategy Default Test Settings
For backtesting purpose, following settings are used:
Initial capital=10000 USD
Default quantity value = 5 % of total capital
Commission value = 0.1 %
Pyramiding isn't included.
Backtesting data never assures that the same results would occur in future and also above settings use very less of total portfolio for trades, which in a way results less maximum drawdown along with less total profit on initial capital too. For example, increasing default quantity value will definity increase maximum drawdown value. The other way is also to use fix contracts in backtesting but it all depends on users general practice. Best option is to explore backtesting results with manually modified settings on different charts, before trusting them for other uses in future.
Usage and In-Detail Backtesting
This strategy has built-in option to enable trade confirmations with Chikou filter which will reduce the total number of trades increasing profit factor.
Symmetrically Weighted Moving Average (SWMA) on input source, may risk repainting in real-time data. Better option is to run a trade on bar close or simply left this optin unchecked.
I've set Chikou filter unchecked to increase number of trades (greater than 100) on higher timeframe (12H) and this can be changed according to your precision requirement and timeframe.
Timeframes lower than 4H usually have more noise. So its better to use higher EDMA and EMA length on lower timeframes which will decrease total number of offsetting trades increasing average total number of bars within a single trade.
Original "Exponentially Deviating Moving Average (MZ EDMA )" Indicator can be found here.
EMA Trend Pro v5.0 5M ONLY — 策略版（1:1出30%+保本）Here is a clear, professional English description you can copy-paste directly (suitable for sharing with friends, investors, brokers, or posting on TradingView):
EMA Trend Pro v5.0 – Strategy Overview
This is a trend-following strategy designed for 15-minute charts on assets like XAUUSD, NASDAQ, BTC, and ETH.
Entry Rules
Buy when the 7, 14, and 21-period EMAs are aligned upward and the 14-period EMA crosses above the 144-period EMA (with ADX > 20 and volume confirmation).
Sell short when the EMAs are aligned downward and the 14-period EMA crosses below the 144-period EMA.
Risk Management
Initial stop-loss is placed at 1.8 × ATR below (long) or above (short) the entry price.
Position size is calculated to risk a fixed percentage of equity per trade.
Profit-Taking & Trade Management
When price reaches 1:1 reward-to-risk, 30% of the position is closed.
At the same moment, the stop-loss for the remaining 70% is moved to the entry price (breakeven).
The remaining position is split:
50% targets 1:2 reward-to-risk
50% targets 1:3 reward-to-risk (allowing big wins during strong trends)
Visualization
Clean colored bars extend to the right showing entry, stop-loss, and three take-profit levels.
Price labels clearly display "Entry", "SL", "TP1 1:1", "TP2 1:2", and "TP3 1:3".
Only the current trade is displayed for a clean chart.
Key Advantages
High win rate due to breakeven protection after 1R
Excellent reward-to-risk ratio that lets winners run
Fully automated, works on any market with clear trends
Professional look, easy to understand and explain
Perfect for swing traders who want consistent profits with limited downside risk.
Feel free to use this description on TradingView, in your trading journal, or when explaining the strategy to others!
If you want a shorter version (e.g., for TradingView description box) or a Chinese version, just let me know — I’ll give it to you right away! 😊
Quantura - Quantified Price Action StrategyIntroduction
“Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices.
Originality & Value
The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of:
Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity.
Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs.
RSI filter: Can be set to normal or aggressive, confirming momentum before trades.
Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies.
EMA filter: Aligns trades with the broader market trend.
Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions.
This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow.
Functionality & Indicators
Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap.
Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection.
RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness.
FVG filter: Adds validation by requiring price interaction with inefficiency zones.
EMA filter: Ensures longs are above EMA and shorts below EMA.
Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status.
Parameters & Customization
Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options.
Liquidity filter: Mode (Run or Sweep), display, and swing length.
RSI: Enable/disable, length, and style (normal or aggressive).
Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles.
EMA: Length, enable/disable, and visualization.
Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing.
Visualization: Custom candle coloring and optional overlay for better clarity.
Default Properties (Strategy Settings)
Initial Capital: 10,000 USD
Position Size: 100% of equity per trade (backtest default)
Commission: 0.1%
Slippage: 1
Pyramiding: 0 (only one position at a time)
Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%.
Backtesting & Performance
Backtests on XPTUSD over 2.5 years with the default settings produced:
164 trades
67.68% win rate
Profit factor: 1.7
Maximum drawdown: 27.81%
These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (164) is sufficient for statistical analysis, results may vary across markets and timeframes.
Risk Management
Three configurable take-profit levels with percentage allocation.
Initial stop-loss based on user-defined percentage.
Dynamic stop-loss that adjusts with market movement.
Break-even logic that shifts stops to entry after predefined gains.
Position sizing based on risk percentage of equity.
This framework allows both conservative and aggressive configurations, depending on user preference.
Limitations & Market Conditions
Works best in volatile and liquid markets such as crypto, metals, indices, and FX.
May produce false signals in low-volume or sideways environments.
Unexpected news or macro events can override technical conditions.
Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use.
Usage Guide
Add “Quantura – Quantified Price Action Strategy” to your chart.
Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe.
Configure risk management: take-profits, stop-loss, and risk-per-trade percentage.
Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions.
Optimize parameters before applying the strategy to different markets.
Author & Access
Developed 100% by Quantura. Published as an Invite-Only script.
Important
This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
EMA Deviation Strategy📌 Strategy: EMA Deviation Strategy
The EMA Deviation Strategy identifies potential reversal points by measuring how far the current price deviates from its Exponential Moving Average (EMA). It dynamically tracks the minimum and maximum deviation levels over a user-defined lookback period, and enters trades when price reaches extreme zones.
🔍 Core Logic:
• Buy Entry: When price deviates significantly below the EMA, approaching the historical minimum deviation — signaling a potential rebound.
• Sell Entry: When price deviates significantly above the EMA, nearing the historical maximum deviation — signaling a possible pullback.
• Optional Take Profit / Stop Loss: Manage risk with customizable exit levels.
⚙️ Customizable Inputs:
• EMA length and lookback period
• Threshold sensitivity for entry signals
• Take profit and stop loss percentages
📈 Best Used For:
• Mean reversion setups
• Assets with cyclical or range-bound behavior
• Identifying short-term overbought/oversold conditions
Daily Investments Index ScalpThis strategy is based on the DIDI index with our own confirmations and calculated SL/TP .
You can change every setting if you want it to use for another pair, but this is fine tuned for NATURALGAS
The entries are taken when:
Long:
- Buy signal from the DIDI indicator
- Long EMA is underneath the Short EMA
- Price must be Above the Long EMA
- TP1 (default) - ATR based first TP is ATR * 1.2 Multiplier
- TP2 (default) - ATR based first TP is ATR * 2 Multiplier
- TP2 SL is the strategy entry price when we hit the first TP
- SL (default) - Latest swing low with a look back of 17 candles
Short:
- Sell signal from the DIDI indicator
- Long EMA is Above the Short EMA
- Price must be Below the Long EMA
- TP1 (default) - ATR based first TP is ATR * 1.2 Multiplier
- TP2 (default) - ATR based first TP is ATR * 2 Multiplier
- TP2 SL is the strategy entry price when we hit the first TP
- SL (default) - Latest swing low with a look back of 17 candles
It's fairly simple, and i think you can use this base so extend your own strategy
Good luck :)
If you have any questions, feel free to comment
CM_SlingShotSystem+_CassicEMA+Willams21EMA13 htc1977 editionThis strategy is a combination of 2 indicators based on EMA(actually x3 EMAs and Williams ind.
We usin this to see where EMA fast is above EMA slow(for long), entry position when price hit fast EMA and exit if trend changes or price overbought, or by stoploss 1%.
The opposite for a short position.
For better result You can change every EMA's, stoploss, Willam's ind and other visualisation in settings.
If You find good combination - please, let me know(if You want).
I will check it with ML, and attach it here.
Original indicators will write in comments
EMA + RSI WITH TP/SL 1 Minute scalping strategy
EMA 50 & EMA 200 dictate direction of entry
EMA 50 above EMA 200 = Long
EMA 50 below EMA 200 = Short
If Long and RSI crossover 25 = Long entry
If Short and RSI crossunder 75 = Short entry
Each trade is currently 1:1.3 risk to reward ratio.
15 pip TP
12 PIP SL
Any suggestions on further improvements /variations are more then welcome.
EMA Cross Strategy v5 (30 lots) (15 min candle only)- safe flip🚀 EMA Cross Strategy v5 (30 Lots) (15 min candle only)— Safe Flip Edition
Fully Automated | Fast | Reliable | Battle-tested
Welcome to a clean, powerful, and automation-friendly EMA crossover system.
This strategy is built for traders who want consistent trend-based entries without the risk of unwanted pyramiding or doubled positions.
🔥 How It Works
This strategy uses a fast EMA (10) crossing a slow EMA (20) to detect trend shifts:
Bullish Crossover → LONG (30 lots)
Bearish Crossover → SHORT (30 lots)
Every opposite signal safely flips the position by first closing the current trade, then opening a fresh position of exactly 30 lots.
No doubling.
No runaway position size.
No surprises.
Just clean, mechanical trend-following.
📈 Why This Strategy Stands Out
Unlike basic EMA crossbots, this version:
✔ Prevents unintended pyramiding
✔ Never over-allocates capital
✔ Works perfectly with webhook-based automation
✔ Produces stable, systematic entries
✔ Executes directional flips with precision
🔍 Backtest Highlights (1-Year)
(Backtests will vary by instrument/timeframe)
1,500+ trades executed
Profit factor above 1.27
Strong trend performance
Balanced long/short behavior
No margin calls
Consistent trade execution
This strategy thrives in trending markets and maintains strict discipline even in choppy conditions.
⚙️ Automation Ready
Designed for automated execution via webhook and API setups on supported platforms.
Just connect, run, and let the bot follow the rules without hesitation.
No emotions.
No overtrading.
No fear or greed.
Pure logic.
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range
Overview:
This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets.
🔍 Strategy Components:
EMA Crossover (Fast/Slow)
Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum.
RSI Filter
RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met.
Long entry requires RSI ≥ Long Threshold
Short entry requires RSI ≤ Short Threshold
ATR-Based SL & TP
Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price.
Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure.
Opening Range Filter (Optional)
If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves.
Session Filters
No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods.
All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options.
⚙️ Built-in Presets:
You can choose one of the built-in ticker-specific presets for optimal conditions:
Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL
SPY 8/28 56 / 26 14 1.4× 4.0×
TSLA 23/27 56 / 33 13 1.4× 3.6×
AAPL 6/13 61 / 26 23 1.4× 2.1×
MSFT 25/32 54 / 26 14 1.2× 2.2×
META 25/32 53 / 26 17 1.8× 2.3×
AMZN 28/32 55 / 25 16 1.8× 2.3×
You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences.
📌 Best Use Case:
This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
Neural Momentum StrategyThis strategy combines Exponential Moving Average (EMA) analysis with a multi-timeframe approach. It uses a neural scoring system to evaluate market momentum and generate precise trading signals. The strategy is implemented in Pine Script v5 and is designed for use on TradingView.
Key Components
The strategy utilizes short-term (10-period) and long-term (25-period) EMAs. It calculates the difference between these EMAs to assess trend direction and strength. A neural scoring system evaluates EMA crossovers (weight: 12 points), trend strength (weight: 10 points), and price acceleration (weight: 4 points). The system implements a score smoothing algorithm using a 10-period EMA.
Multi-timeframe Analysis
The strategy automatically selects a higher timeframe based on the current chart timeframe. It calculates scores for both the current and higher timeframes, then combines these scores using a weighted average. The higher timeframe factor ranges from 3 to 6, depending on the current timeframe.
Trading Logic
Entry occurs when the final combined score turns positive after a change. Exit happens when the final combined score turns negative after a change. The strategy recalculates scores on each bar, ensuring responsive trading decisions.
Risk Management
An optional adaptive stop-loss system based on Average True Range (ATR) is available. The default ATR period is 10, and the stop factor is 1.2. Stop levels are dynamically adjusted on the higher timeframe.
Customization Options
Users can adjust EMA periods, signal line period, scoring weights, and enable/disable multi-timeframe analysis. The strategy allows setting specific date ranges for backtesting and deployment.
Position Sizing
The strategy uses a percentage-of-equity position sizing method, with a default of 30% of account equity per trade.
Code Structure
The strategy is built using TradingView's strategy framework. It employs efficient use of the request.security() function for multi-timeframe analysis. The main calculation function, calculate_score(), computes the neural score based on EMA differences and acceleration.
Performance Considerations
The strategy adapts to various market conditions through its multi-faceted scoring system. Multi-timeframe analysis helps filter out noise and identify stronger trends. The neural scoring approach aims to capture subtle market dynamics often missed by traditional indicators.
Limitations
Performance may vary across different markets and timeframes. The strategy's effectiveness relies on proper calibration of its numerous parameters. Users should thoroughly backtest and forward test before live implementation.
To summarize, the Neural Momentum Strategy represents a sophisticated approach to market analysis. It combines traditional technical indicators with advanced scoring techniques and multi-timeframe analysis. This strategy is designed for traders seeking a data-driven and adaptive method. It aims to identify high-probability trading opportunities across various market conditions.
This Neural Momentum Strategy is for informational and educational purposes only. It should not be considered financial advice. The strategy may exhibit slight repainting behavior due to the nature of multi-timeframe analysis and the use of the request.security() function. Historical values might change as new data becomes available.
Trading carries a high level of risk, and may not be suitable for all investors. Before deciding to trade, you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment. Therefore, you should not invest money that you cannot afford to lose.
Past performance is not indicative of future results. The author and TradingView are not responsible for any losses incurred as a result of using this strategy. Always exercise caution when using this or any trading strategy, and thoroughly test it before implementing in live trading scenarios.
Users are solely responsible for any trading decisions they make based on this strategy. It is strongly recommended that you seek advice from an independent financial advisor if you have any doubts.
Bollinger Bands Modified (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses two indicators Bollinger Bands and EMA (optional for EMA).
Calculates Bollinger Bands, EMA, highest high, and lowest low values based on the input parameters, evaluating the conditions to determine potential long and short entry signals.
The conditions include checks for crossovers and crossunders of the price with the upper and lower Bollinger Bands, as well as the position of the price relative to the EMA.
The script also incorporates the option to add an inside bar pattern check for additional information.
Entry Position
Long Position:
Price cross over the superior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is above EMA.
Short Position:
Price cross under the inferior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is under EMA.
Risk Management
Stop Loss:
The stop loss is calculated based on the input highest high (for short position) and lowest low (for long position).
It gets the length based on the input from the last candles to set which is the highest high and which is the lowest low.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Uptrend and Oversold Index Swing Trading System 8H--- Foreword ---
The Overbought and Oversold Index Swing Trading System or short: I11L Hypertrend primarily uses money management Strategies, EMA and SMA and my momentum Ideas for trying to produce satisfactory Alpha over a timespan of multiple years.
--- How does it Work? ---
It uses 20 different EMA's and SMA's to produce a score for each Bar.
It will credit one Point If the EMA is above the SMA.
A high score means that there is a strong Uptrend.
Spotting the strong Uptrend early is important.
The I11L Hypertrend System trys to spot the "UPTREND" by checking for a crossover of the Score(EMA) / Score(SMA).
A low score means that there is a strong Downtrend.
Its quite common to see a reversal to the mean after a Downtrend and spotting the bottom is important.
The System trys to spot the reversal, or "OVERSOLD" state by a crossunder of the Score(EMA) / Score(SMA).
--- What can i customize? ---
-> Trading Mode: You can choose between two different trading modes, Oversold and Overbought(trend) and Random Buys to check if your systems Profitfactor is actually better then market.
-> Work with the total equity: The system uses the initial capital per default for Backtesting purposes but seeing the maximum drawdown in a compounding mode might help!
-> Use a trailing SL: A TSL trys to not lose too much if the trade goes against your TP
-> Lookbackdistance for the Score: A higher Lookbackdistance results in a more lagging indicator. You have to find the balance between the confirmation of the Signal and the frontrunning.
-> Leverage: To see how your strategie and your maximum Drawdown with the total equity mode enabled would have performed.
-> Risk Capital per Trade unleveraged: How much the underlying asset can go against your position before the TSL hits, or the SL if no TSL is set.
-> TPFactor: Your risk/reward Ratio. If you risk 3% and you set the ratio to 1.2, you will have a TP at 3 * 1.2 = 3.6%
-> Select Date: Works best in the 8H Timeframe for CFD's. Good for getting a sense of what overfitting actually means and how easy one can fool themself, find the highest Profitfactor setting in the first Sector (Start - 2012) and then see if the second Sector (2012 - Now) produces Alpha over the Random Buy mode.
--- I have some questions about the System ---
Dear reader, please ask the question in the comment Section and i will do my best to assist you.
PMA Strategy IdeaThis strategy idea uses three EMAs on HLC/3 data, know as PMA(Pivot Moving Average). This strategy is very useful in trending instruments on 1W and 1D timeframes. This is the implementation used in QuantCT app. The study version of this idea is published in public library as ACD PMA .
You can set operation mode to be Long/Short or long-only.
You also can set a fixed stop-loss or ignore it so that the strategy act solely based on entry and exit signals.
Trade Idea
When all EMAs are rising, market is considered rising (bullish) and the plotted indicator becomes green.
When all EMAs are falling, market is considered falling (bearish) and the plotted indicator becomes red.
Otherwise, market is considered ranging and the plotted indicator becomes orange.
Entry/Exit rules
Enter LONG if all EMAs are rising (i.e. when the plotted indicator becomes green).
Enter SHORT if all EMAs are falling (i.e. when the plotted indicator becomes red).
EXIT market if none of the above (i.e. when the plotted indicator becomes orange).
CAUTION
It's just a bare trading idea - a profitable one. However, you can enhance this idea and turn it into a full trading strategy with enhanced risk/money management and optimizing it, and you ABSOLUTELY should do this!
DON'T insist on using Long/Short mode on all instruments! This strategy performs much better in Long-Only mode on many (NOT All) trending instruments (Like BTC , ETH, etc.).
STOCH&EMA Strategy with a trailing stop EMA'S dictate direction of entry
50 EMA above 200 EMA = LONG
50 EMA below 200 EMA = SHORT
Stoch 15,20,5
When LONG and "K" crosses over signal line "D Underneath the value of 40 = Enter Long
When SHORT and "K" crosses under signal line "D" Above the value of 60 = Enter Short
Risk managment
Trailing profit at 21 pips with a 1 pip offset ( attempting to catch any further moves of breaks)
Stop loss 20 pips
Any suggestions on how to improve this strategy is always welcome
35EMA Cross BuyAndSell Strategy + RIBBON [d3nv3r]This strategy allow the user to move the EMA which control the Buy&Sell Strategy and show the EMA ribbon that can be found in the Template area.
Buy showing the ribbon and letting the user to adjust the EMA signaling the B&S strat the user can create an elaborated strategy for buyPoint and sellPoint.
The 35EMA Cross is choosen by default but I recommend to move it to find best Sell point and best Buy point as you would not react on the same EMA for a Buy signal and a Sell Signal..
It would be good to have buy signal on a EMA and the sell signal on another but that's for another Strategy to be shared.
Let me know by commenting what you would like for the next one !
Pro Bollinger Bands Strategy [Breno]This strategy excels in highly volatile financial instruments, including cryptocurrencies, high-beta stocks, commodity futures, and certain exchange-traded funds (ETFs) that exhibit clear mean-reversion characteristics around their Bollinger Bands. The system's ability to utilize scaling (position averaging) and an ATR-based stop loss makes it particularly effective in markets with significant price swings, allowing the trader to capture profits from price extremes while managing increased volatility-related risk.
Core Strategy Logic
This Strategy implements a comprehensive trend-following and mean-reversion strategy primarily leveraging the Bollinger Bands (BB) indicator for entry and exit signals, complemented by an Average True Range (ATR)-based Stop Loss mechanism and an optional EMA filter. It is designed with robust features for capital management, including configurable leverage and a sophisticated position averaging (scaling) system.
Long Entry: A long position is initiated when the closing price crosses over the Lower Bollinger Band (ta.crossover(close,lowerBB)). This signals a potential mean-reversion opportunity following a price dip.
Short Entry: A short position is initiated when the closing price crosses under the Upper Bollinger Band (ta.crossunder(close,upperBB)). (Note: Short entries are disabled by default in the script inputs).
Exit Conditions (Profit Target): Long positions aim to exit upon interaction with the Upper Bollinger Band. Users can select from three exit methods:
"Close When Touch": Exits when close≥upperBB.
"Close Above then Below": Exits when the previous close was above the upper band, and the current close is below it (a reversal signal).
"High Above": Exits when high>upperBB. The strategy features an optional profitOnly setting, which restricts all exits to only occur if the trade is currently in profit (i.e., close is above the strategy.position_avg_price for longs).
Key Features and Customization
Bollinger Bands & Filters -
Customizable BB Parameters: The Length and Deviation of the Bollinger Bands are fully adjustable, allowing users to fine-tune the sensitivity of the entry and exit signals.
Optional EMA Filter: An optional EMA Filter can be enabled to align entries with the prevailing trend, where a Long entry is only permitted if close≥EMA(EmaFilterRange).
Risk and Capital Management -
Equity Allocation: Position size is dynamically calculated based on a Percentage of Equity (capitalPerc) combined with the set Leverage multiplier.
Dynamic Stop Loss (ATR-Based):
An optional Stop Loss (SL) is calculated using a multiple (slAtrInput) of the Average True Range (ATR).
The SL is set relative to the entry price upon trade activation, providing a volatility-adjusted risk management layer.
Position Averaging (Scaling): The script supports the addition of multiple units (pyramiding) to an existing position based on three user-selected criteria:
"No": No averaging.
"Percent": Adds to the position if the price has dropped by a set percentage (addPct) from the average price.
"ATR": Adds to the position if the current price is significantly below a calculated ATR-based support level from the average price.
Quantura - Quantitative AlgorythmIntroduction
“Quantura – Quantitative Algorithm” is an invite-only Pine Script strategy designed for multi-timeframe analysis, combining technical filters with user-adjustable fundamental sentiment. It was primarily developed for cryptocurrency markets but can also be applied across other assets such as Forex, stocks, and indices. The goal is to generate structured trade signals through a confluence of techniques rather than relying on a single indicator.
Originality & Value
Quantura is not a simple mashup of indicators. Its originality comes from how multiple layers of analysis are integrated into a single decision framework . Instead of showing indicators separately, the strategy only issues trades when several conditions align simultaneously:
RSI entry triggers confirm overbought/oversold reversals.
Market structure on a higher timeframe confirms trend direction.
Order block detection highlights zones of concentrated supply and demand.
Premium/Discount zones identify potential over- and undervaluation.
HTF EMA provides trend confirmation.
Optional candlestick patterns strengthen reversal or continuation signals.
An optional correlation filter compares the main asset to a reference instrument.
This design forces agreement between different methodologies (momentum, structure, value, volume, sentiment), which reduces noise compared to using them in isolation.
Functionality & Indicators
Entry trigger: RSI exits from extreme zones.
Filters: Only valid when all selected filters (HTF structure, EMA, order blocks, premium/discount, candlesticks, correlation, volume) confirm the direction.
Fundamental bias: User-defined sentiment and analysis settings (bullish, bearish, neutral) influence whether long or short trades are permitted.
Exits: ATR-based take profit and stop loss, with optional breakeven, opposite-signal exit, and session-end exit.
Visualization: Buy/Sell markers, trend-colored candles, and an optional dashboard summarizing indicator status.
Parameters & Customization
Timeframes: Independent HTF and LTF selection.
Trading direction: Long / Short / Both.
Session and weekday filters.
RSI length and thresholds.
Filters: HTF structure, order blocks, premium/discount, EMA, candlestick, ATR volatility, volume zones, correlation.
Exit rules: ATR multipliers for TP/SL, breakeven logic, session-end exit, opposite-signal exit.
Visuals: Toggle signals, candles, dashboard, custom colors.
Default Properties (Strategy Settings)
Initial Capital: 100,000 USD
Position Size: 15% of equity per trade
Commission: 0.25%
Slippage: enabled
Pyramiding: 0 (one position at a time)
Note: The position sizing of 15% equity per trade is intentionally set for backtesting demonstration. In real trading, risking this much is considered aggressive. Most traders prefer to risk 1-5% of equity, and rarely above 10%.
Backtesting & Performance
Backtests on BTCUSD (2 years) with the above defaults showed:
112 trades
Win rate: 40%
Profit factor: 1.4
Maximum drawdown: 34%
These results illustrate how the confluence model behaves, but they are not predictive of future performance . The trade sample size (72 trades) is below the 100+ usually recommended for statistical robustness. Users should re-test with their own preferred symbols, settings, and timeframes.
Risk Management
ATR-based stops and targets scale with volatility.
Commission and slippage are included by default for realistic modeling.
Opposite-signal exit helps capture trend reversals.
Session-end exit can close intraday positions before illiquid hours.
Breakeven option protects profits when available.
Although the default allocation uses 15% per trade for demonstration, this is not a recommendation. Users are encouraged to adjust risk sizing downwards to sustainable levels (commonly 1-5%).
Limitations & Market Conditions
Performs best in volatile, liquid markets (e.g., crypto).
May struggle in prolonged sideways markets with low volatility.
News events and fundamentals outside user inputs can override signals.
Backtests below 100 trades should be considered exploratory, not statistically conclusive.
Usage Guide
Add “Quantura – Quantitative Algorithm” to your chart in strategy mode.
Select HTF and LTF timeframes, trading direction, and session filters.
Configure confluence filters (structure, EMA, order blocks, premium/discount, candlestick, correlation, volume).
Set sentiment and analysis bias in fundamental settings.
Adjust ATR multipliers and exits.
Review buy/sell signals and analyze performance in the Strategy Tester.
Author & Access
Developed 100% by Quantura . Distributed as an Invite-Only script . Details are provided in the Author’s Instructions field.
Important: This description complies with TradingView’s Script Publishing Rules and House Rules. It does not guarantee profitability, avoids unrealistic claims, and explains how the strategy integrates multiple methods into a coherent decision framework.
Script_Algo - High Low Range MA Crossover Strategy🎯 Core Concept
This strategy uses modified moving averages crossover, built on maximum and minimum prices, to determine entry and exit points in the market. A key advantage of this strategy is that it avoids most false signals in trendless conditions, which is characteristic of traditional moving average crossover strategies. This makes it possible to improve the risk/reward ratio and, consequently, the strategy's profitability.
📊 How the Strategy Works
Main Mechanism
The strategy builds 4 moving averages:
Two senior MAs (on high and low) with a longer period
Two junior MAs (on high and low) with a shorter period
Buy signal 🟢: when the junior MA of lows crosses above the senior MA of highs
Sell signal 🔴: when the junior MA of highs crosses below the senior MA of lows
As seen on the chart, it was potentially possible to make 9X on the WIFUSDT cryptocurrency pair in just a year and a half. However, be careful—such results may not necessarily be repeated in the future.
Special Feature
Position closing priority ❗: if an opposite signal arrives while a position is open, the strategy first closes the current position and only then opens a new one
⚙️ Indicator Settings
Available Moving Average Types
EMA - Exponential MA
SMA - Simple MA
SSMA - Smoothed MA
WMA - Weighted MA
VWMA - Volume Weighted MA
RMA - Adaptive MA
DEMA - Double EMA
TEMA - Triple EMA
Adjustable Parameters
Senior MA Length - period for long-term moving averages
Junior MA Length - period for short-term moving averages
✅ Advantages of the Strategy
🛡️ False Signal Protection - using two pairs of modified MAs reduces the number of false entries
🔄 Configuration Flexibility - ability to choose MA type and calculation periods
⚡ Automatic Switching - the strategy automatically closes the current position when receiving an opposite signal
📈 Visual Clarity - all MAs are displayed on the chart in different colors
⚠️ Disadvantages and Risks
📉 Signal Lag - like all MA-based strategies, it may provide delayed signals during sharp movements
🔁 Frequent Switching - in sideways markets, it may lead to multiple consecutive position openings/closings
📊 Requires Optimization - optimal parameters need to be selected for different instruments and timeframes
💡 Usage Recommendations
Backtest - test the strategy's performance on historical data
Optimize Parameters - select MA periods suitable for the specific trading instrument
Use Filters - add additional filters to confirm signals
Manage Risks - always use stop-loss and take-profit orders.
You can safely connect to the exchange via webhook and enjoy trading.
Good luck and profits to everyone!!
TradeBuilderOverview
TradeBuilder is an ever-growing toolbox that lets you combine and compound any number of bundled indicators and algorithms to create a compound strategy. At launch, we're including two Moving Averages (SMA, EMA), RSI, and Stochastic Oscillator, with many more to come. You can use any combination of indicators, be it just one, two, or all.
Key Concepts
Indicator Integration: Tradebuilder allows the use of Moving Averages, RSI, and Stochastic Oscillators, with customizable parameters for each. More indicators to come.
Mode Selection : Choose between Confirm Trend Mode (using indicators to confirm trends) and Momentum Mode (using indicators to spot reversals).
Trade Flexibility : Offers options for both long and short trades, enabling diverse trading strategies.
Customizable Inputs : Easily toggle indicators on or off and adjust specific settings like periods and thresholds.
Signal Generation : Combines multiple conditions to generate entry and exit signals.
Input Parameters:
Moving Average (MA):
use_ma : Enable this to include the Moving Average in your strategy.
ma_cross_type : Choose between "Close/MA" (price crossing the MA) or "MA/MA" (one MA crossing another).
ma_length : Set the period for the primary MA.
ma_type : Choose between "SMA" (Simple Moving Average) or "EMA" (Exponential Moving Average).
ma_length2 : Set the period for the secondary MA if using the "MA/MA" cross type.
ma_type2 : Set the type for the secondary MA.
Relative Strength Index (RSI):
use_rsi : Enable this to include RSI in your strategy.
rsi_length : Set the period for RSI calculation.
rsi_overbought : Define the overbought level.
rsi_oversold : Define the oversold level.
Stochastic Oscillator:
use_stoch : Enable this to include the Stochastic Oscillator in your strategy.
stoch_k : Set the %K period.
stoch_d : Set the %D period.
stoch_smooth : Define the smoothing factor.
stoch_overbought : Set the overbought level.
stoch_oversold : Set the oversold level.
Confirmation or Momentum Mode:
confirm_trend : Set this to true to use RSI and Stochastic Oscillator to confirm trends (long when above overbought, short when below oversold). Set to false to trade on momentum (short when above overbought, long when below oversold).
Tip: When set to false and used with just momentum oscillators like Stochastic or RSI, it's geared toward scalping as it essentially becomes momentum trading.
Trade Directions:
trade_long : Enable to allow long trades.
trade_short : Enable to allow short trades.
Example Strategy on E-mini S&P 500 Index Futures ( CME_MINI:ES1! ), 1-minute Chart
Let’s say you want to create a strategy to go long when:
A 5-period SMA crosses above a 100-period EMA.
RSI is above 20.
The Stochastic Oscillator is above 95.
Trend Confirmation Mode is on.
For short:
A 5-period SMA crosses below a 100-period EMA.
RSI is below 45.
The Stochastic Oscillator is below 5.
Trend Confirmation Mode is on.
Here’s how you would set it up in Tradebuilder:
use_ma = true
ma_cross_type = "MA/MA"
ma_length = 5
ma_type = "SMA"
ma_length2 = 100
ma_type2 = "EMA"
use_rsi = true
rsi_length = 14
rsi_overbought = 20
rsi_oversold = 45
use_stoch = true
stoch_k = 8
stoch_d = 1
stoch_smooth = 1
stoch_overbought = 95
stoch_oversold = 5
confirm_trend = true
trade_long = true
trade_short = false
Alerts
Here is how to set TradeBuilder alerts: open a TradingView chart, attach TradeBuilder, right-click on chart -> Add Alert. Condition: Symbol (e.g. NQ) >> TradeBuilder >> Open-Ended Alert >> Once Per Bar Close.
Development Roadmap
We plan to add many more compoundable indicators to TradeBuilder over the coming months from all walks of technical analysis, including Volume, Volatility, Trend Detection/Validation, Momentum, Divergences, Chart Patterns, Support/Resistance Analysis. etc.
