EMA bands + leledc + bollinger bands trend following strategy v2The basics:
In its simplest form, this strategy is a positional trend following strategy which enters long when price breaks out above "middle" EMA bands and closes or flips short when price breaks down below "middle" EMA bands. The top and bottom of the middle EMA bands are calculated from the EMA of candle highs and lows, respectively.
The idea is that entering trades on breakouts of the high EMAs and low EMAs rather than the typical EMA based on candle closes gives a bit more confirmation of trend strength and minimizes getting chopped up. To further reduce getting chopped up, the strategy defaults to close on crossing the opposite EMA band (ie. long on break above high EMA middle band and close below low EMA middle band).
This strategy works on all markets on all timeframes, but as a trend following strategy it works best on markets prone to trending such as crypto and tech stocks. On lower timeframes, longer EMAs tend to work best (I've found good results on EMA lengths even has high up to 1000), while 4H charts and above tend to work better with EMA lengths 21 and below.
As an added filter to confirm the trend, a second EMA can be used. Inputting a slower EMA filter can ensure trades are entered in accordance with longer term trends, inputting a faster EMA filter can act as confirmation of breakout strength.
Bar coloring can be enabled to quickly visually identify a trend's direction for confluence with other indicators or strategies.
The goods:
Waiting for the trend to flip before closing a trade (especially when a longer base EMA is used) often leaves money on the table. This script combines a number of ways to identify when a trend is exhausted for backtesting the best early exits.
"Delayed bars inside middle bands" - When a number of candle's in a row open and close between the middle EMA bands, it could be a sign the trend is weak, or that the breakout was not the start of a new trend. Selecting this will close out positions after a number of bars has passed
"Leledc bars" - Originally introduced by glaz, this is a price action indicator that highlights a candle after a number of bars in a row close the same direction and result in greatest high/low over a period. It often triggers when a strong trend has paused before further continuation, or it marks the end of a trend. To mitigate closing on false Leledc signals, this strategy has two options: 1. Introducing requirement for increased volume on the Leledc bars can help filter out Leledc signals that happen mid trend. 2. Closing after a number of Leledc bars appear after position opens. These two options work great in isolation but don't perform well together in my testing.
"Bollinger Bands exhaustion bars" - These bars are highlighted when price closes back inside the Bollinger Bands and RSI is within specified overbought/sold zones. The idea is that a trend is overextended when price trades beyond the Bollinger Bands. When price closes back inside the bands it's likely due for mean reversion back to the base EMA in which this strategy will ideally re-enter a position. Since the added RSI requirements often make this indicator too strict to trigger a large enough sample size to backtest, I've found it best to use "non-standard" settings for both the bands and the RSI as seen in the default settings.
"Buy/Sell zones" - Similar to the idea behind using Bollinger Bands exhaustion bars as a closing signal. Instead of calculating off of standard deviations, the Buy/Sell zones are calculated off multiples of the middle EMA bands. When trading beyond these zones and subsequently failing back inside, price may be due for mean reversion back to the base EMA. No RSI filter is used for Buy/Sell zones.
If any early close conditions are selected, it's often worth enabling trade re-entry on "middle EMA band bounce". Instead of waiting for a candle to close back inside the middle EMA bands, this feature will re-enter position on only a wick back into the middle bands as will sometimes happen when the trend is strong.
Any and all of the early close conditions can be combined. Experimenting with these, I've found can result in less net profit but higher win-rates and sharpe ratios as less time is spent in trades.
The deadly:
The trend is your friend. But wouldn't it be nice to catch the trends early? In ranging markets (or when using slower base EMAs in this strategy), waiting for confirmation of a breakout of the EMA bands at best will cause you to miss half the move, at worst will result in getting consistently chopped up. Enabling "counter-trend" trades on this strategy will allow the strategy to enter positions on the opposite side of the EMA bands on either a Leledc bar or Bollinger Bands exhaustion bar. There is a filter requiring either a high/low (for Leledc) or open (for BB bars) outside the selected inner or outer Buy/Sell zone. There are also a number of different close conditions for the counter-trend trades to experiment with and backtest.
There are two ways I've found best to use counter-trend trades
1. Mean reverting scalp trades when a trend is clearly overextended. Selecting from the first 5 counter-trend closing conditions on the dropdown list will usually close the trades out quickly, with less profit but less risk.
2. Trying to catch trends early. Selecting any of the close conditions below the first 5 can cause the strategy to behave as if it's entering into a new trend (from the wrong side).
This feature can be deadly effective in profiting from every move price makes, or deadly to the strategy's PnL if not set correctly. Since counter-trend trades open opposite the middle bands, a stop-loss is recommended to reduce risk. If stop-losses for counter-trend trades are disabled, the strategy will hold a position open often until liquidation in a trending market if th trade is offsides. Note that using a slower base EMA makes counter-trend stop-losses even more necessary as it can reduce the effectiveness of the Buy/Sell zone filter for opening the trades as price can spend a long time trending outside the zones. If faster EMAs (34 and below) are used with "Inner" Buy/Zone filter selected, the first few closing conditions will often trigger almost immediately closing the trade at a loss.
The niche:
I've added a feature to default into longs or shorts. Enabling these with other features (aside from the basic long/short on EMA middle band breakout) tends to break the strategy one way or another. Enabling default long works to simulate trying to acquire more of the asset rather than the base currency. Enabling default short can have positive results for those high FDV, high inflation coins that go down-only for months at a time. Otherwise, I use default short as a hedge for coins that I hold and stake spot. I gain the utility and APR of staking while reducing the risk of holding the underlying asset by maintaining a net neutral position *most* of the time.
Disclaimer:
This script is intended for experimenting and backtesting different strategies around EMA bands. Use this script for your live trading at your own risk. I am a rookie coder, as such there may be errors in the code that cause the strategy to behave not as intended. As far as I can tell it doesn't repaint, but I cannot guarantee that it does not. That being said if there's any question, improvements, or errors you've found, drop a comment below!
在腳本中搜尋"stop loss"
GRID SPOT TRADING ALGORITHM - GRID BOT TRADING STRATEGYGRID SPOT TRADING ALGORITHM : LONG ONLY STRATEGY OPEN SOURCE
This is a long only strategy for spot assets.
HOW IT WORKS
Grid trading is a trading strategy where an investor creates a so-called "price grid". The basic idea of the strategy is to repeatedly buy at the pre-specified price and then wait for the price to rise above that level and then sell the position (and vice versa with shorting or hedging).
FEATURES
Grids: This algorithm has a total of 10 grids.
Take profit: The trader can increase or decrease the distance between the grids from the User Interface panel, the distance between one grid and another represents the take profit.
Management: The algorithm buys 10% of the capital every time the price breaks down a grid and sells during a rise to the next higher grid. The initial capital is invested in 10 sizes which represent 10% of the capital per trade.
Stop Loss: The algorithm knows no stop loss as long as it is not activated from the User Interface panel. By activating the stop loss from the User Interface panel the algorithm will insert a close condition on all trades which will be calculated from the last lower grid.
Trades: Trades are opened only if the price is within the grid. If the market leaves the grid the algorithm will not buy new positions or sell new positions.
Optimal market conditions: The favorable market for this algorithm is the sideways market.
LIMITATIONS OF THE MODEL
The trader must take into account that this is a static model. It only works perfectly well if the market is in a sideways phase and incurs heavy losses if the market takes a downward trend. The model is unusable for an uptrend. The trader must therefore carefully analyze the market where he intends to use this strategy, making sure that the price is in a sideways phase.
USES
Indispensable research and backtesting tool for those using bots for their investments. The algorithm produces a backtesting of the strategy for past history. It is used by professional traders to understand if this strategy has been profitable on a market and what parameters to use for bots using this strategy (Kucoin, Binance etc.).
If you would like to develop your own algorithm with customized conditions based on a grid strategy, please contact us.
If you need help in using this tool, please contact us without hesitation.
Breakout Trend Trading Strategy - V1Strategy in nutshell:
This strategy is made to be used in daily time-frames. Works better on trending instruments where volume is available. Hence, this is more suitable for trending shares rather than currencies, commodities and indexes where volume data is either not present or not reliable.
Breakout signifies the continuation of trend. Hence, trade in the direction of breakouts. Breakouts are calculated based on high volume and price movement in a day. This will be combined with few other conditions to generate buy and sell signals along with stop and compound targets. Supertrend is used for trend bias. Our buy and sell targets do not directly depend on the bias. But, entry criteria in opposite trend is made much difficult than that of trend direction. Further explanation of method and input parameters are explained below.
Backtesting parameters :
Capital and position sizing : Capital and position sizing parameters are set to test investing 2000 wholly on certain stock without compounding.
Initial Capital : 2000
Order Size : 100% of equity
Pyramiding : 1
ExitOnSignal : If unchecked exit is triggered solely on trailing stop
Trade Direction : Long, Short or All. Short condition is riskier than long conditions and often results in losses as per my observation. On most of the stocks trending up, strategy will not generate any short signals. This is achieved by comparing yearly high lows to previous two years to decide whether to allow short or long entries.
allowImmediateCompound : Applicable only if compounding/pyramiding is enabled in trade. If checked allows to place compounding orders immediately. If unchecked, it waits for stopline to cross order price before placing next compound.
Display Mode :
Targets : Whenever breakout happens, show marker for upTarget and downTarget
TargetChannel : Show up target and downtarget as a channel
Target With Stop : Along with targets, show also stop levels for breakouts
Up Channel : Channel created from UpTarget and respective stops
Down Channel : Channel created from DownTarget and respective stops
ShowTrailingStop : Shows trailing stop and compound lines when there is a trading position.
ShowTargetLevels : Shows Buy Sell target levels along with stop and compound lines. Trades are done as market orders. Hence, target levels are displayed after strategy makes the trade. Since only one order allowed per side without compounding, target, stop and compound levels are shown sometimes even without trade being made. These can be considered as entry levels if there is no existing position.
ShowPreviousLevels : Shows previous buy/sell target levels. When enabled, layout can look messy.
StopMultiplyer: To Set trailing stop loss.
BacktestYears: Number of years to include in backtest
So far my test cases are:
Positive : AAPL, AMZN, TSLA, RUN, VRT, ASX:APT
Negative Test Cases: WPL, WHC, NHC, WOW, COL, NAB (All ASX stocks)
Special test case: WDI
Negative test cases still show losses in backtesting. I have attempted including many conditions to eliminate or reduce the loss. But, further efforts has resulted in reduction in profits in positive cases as well. Still experimenting. Will update whenever I find improvements. Comments and suggestions welcome :)
Two Take Profit StrategyThis script is for research purposes only. I am not a financial advisor.
Entry Condition
This strategy is based on two take profit targets and scaling out strategy. The entry rule is very simple. Whenever the EMA crossover WMA, the long trade is taken and vice versa.
Take Profit and Stop Loss
The first take profit is set at 20 pips above the long entry and the second take profit is set at 40 pips above the long entry. Meanwhile, the stop loss is set at 20 pips below the long entry.
Money Management
When the first take profit is achieved, half of the position is closed. The rest of the position is open to achieve either second take profit or stop loss.
There are three outcomes when using this strategy. Let's say you enter the trade with 200 lot size and you are risking 2% of your equity.
1. The first outcome is when the price hits stop loss, you lose the entire 2%.
2. The second outcome is when the price hits the first take profit and you close half of your position. Meaning that you have gained 1%. Then you let the trade running and eventually it hits stop loss. The total loss is 0% because the remaining lot size which is 200/2=100 times by 20pips is 1%. You have gained the earlier 1% and then loss 1%. At this point, you are at break even.
3. The third outcome is similar to the second out but instead of hiring stop loss, the trade is running to your favor and hits the second take profit.
Therefore, you gained 1% from the first take profit and you gained another 2% for the second take profit. Your total gained is 3%
Summary
The reason behind this strategy is to minimize risk. with normal strategy, you only have two outcomes which are either win or loss. With this strategy, you have three outcomes which are win, loss or break even.
Lorentzian Classification - Advanced Trading DashboardLorentzian Classification - Relativistic Market Analysis
A Journey from Theory to Trading Reality
What began as fascination with Einstein's relativity and Lorentzian geometry has evolved into a practical trading tool that bridges theoretical physics and market dynamics. This indicator represents months of wrestling with complex mathematical concepts, debugging intricate algorithms, and transforming abstract theory into actionable trading signals.
The Theoretical Foundation
Lorentzian Distance in Market Space
Traditional Euclidean distance treats all feature differences equally, but markets don't behave uniformly. Lorentzian distance, borrowed from spacetime geometry, provides a more nuanced similarity measure:
d(x,y) = Σ ln(1 + |xi - yi|)
This logarithmic formulation naturally handles:
Scale invariance: Large price moves don't overwhelm small but significant patterns
Outlier robustness: Extreme values are dampened rather than dominating
Non-linear relationships: Captures market behavior better than linear metrics
K-Nearest Neighbors with Relativistic Weighting
The algorithm searches historical market states for patterns similar to current conditions. Each neighbor receives weight inversely proportional to its Lorentzian distance:
w = 1 / (1 + distance)
This creates a "gravitational" effect where closer patterns have stronger influence on predictions.
The Implementation Challenge
Creating meaningful market features required extensive experimentation:
Price Features: Multi-timeframe momentum (1, 2, 3, 5, 8 bar lookbacks) Volume Features: Relative volume analysis against 20-period average
Volatility Features: ATR and Bollinger Band width normalization Momentum Features: RSI deviation from neutral and MACD/price ratio
Each feature undergoes min-max normalization to ensure equal weighting in distance calculations.
The Prediction Mechanism
For each current market state:
Feature Vector Construction: 12-dimensional representation of market conditions
Historical Search: Scan lookback period for similar patterns using Lorentzian distance
Neighbor Selection: Identify K nearest historical matches
Outcome Analysis: Examine what happened N bars after each match
Weighted Prediction: Combine outcomes using distance-based weights
Confidence Calculation: Measure agreement between neighbors
Technical Hurdles Overcome
Array Management: Complex indexing to prevent look-ahead bias
Distance Calculations: Optimizing nested loops for performance
Memory Constraints: Balancing lookback depth with computational limits
Signal Filtering: Preventing clustering of identical signals
Advanced Dashboard System
Main Control Panel
The primary dashboard provides real-time market intelligence:
Signal Status: Current prediction with confidence percentage
Neighbor Analysis: How many historical patterns match current conditions
Market Regime: Trend strength, volatility, and volume analysis
Temporal Context: Real-time updates with timestamp
Performance Analytics
Comprehensive tracking system monitors:
Win Rate: Percentage of successful predictions
Signal Count: Total predictions generated
Streak Analysis: Current winning/losing sequence
Drawdown Monitoring: Maximum equity decline
Sharpe Approximation: Risk-adjusted performance estimate
Risk Assessment Panel
Multi-dimensional risk analysis:
RSI Positioning: Overbought/oversold conditions
ATR Percentage: Current volatility relative to price
Bollinger Position: Price location within volatility bands
MACD Alignment: Momentum confirmation
Confidence Heatmap
Visual representation of prediction reliability:
Historical Confidence: Last 10 periods of prediction certainty
Strength Analysis: Magnitude of prediction values over time
Pattern Recognition: Color-coded confidence levels for quick assessment
Input Parameters Deep Dive
Core Algorithm Settings
K Nearest Neighbors (1-20): More neighbors create smoother but less responsive signals. Optimal range 5-8 for most markets.
Historical Lookback (50-500): Deeper history improves pattern recognition but reduces adaptability. 100-200 bars optimal for most timeframes.
Feature Window (5-30): Longer windows capture more context but reduce sensitivity. Match to your trading timeframe.
Feature Selection
Price Changes: Essential for momentum and reversal detection Volume Profile: Critical for institutional activity recognition Volatility Measures: Key for regime change detection Momentum Indicators: Vital for trend confirmation
Signal Generation
Prediction Horizon (1-20): How far ahead to predict. Shorter horizons for scalping, longer for swing trading.
Signal Threshold (0.5-0.9): Confidence required for signal generation. Higher values reduce false signals but may miss opportunities.
Smoothing (1-10): EMA applied to raw predictions. More smoothing reduces noise but increases lag.
Visual Design Philosophy
Color Themes
Professional: Corporate blue/red for institutional environments Neon: Cyberpunk cyan/magenta for modern aesthetics
Matrix: Green/red hacker-inspired palette Classic: Traditional trading colors
Information Hierarchy
The dashboard system prioritizes information by importance:
Primary Signals: Largest, most prominent display
Confidence Metrics: Secondary but clearly visible
Supporting Data: Detailed but unobtrusive
Historical Context: Available but not distracting
Trading Applications
Signal Interpretation
Long Signals: Prediction > threshold with high confidence
Look for volume confirmation
- Check trend alignment
- Verify support levels
Short Signals: Prediction < -threshold with high confidence
Confirm with resistance levels
- Check for distribution patterns
- Verify momentum divergence
- Market Regime Adaptation
Trending Markets: Higher confidence in directional signals
Ranging Markets: Focus on reversal signals at extremes
Volatile Markets: Require higher confidence thresholds
Low Volume: Reduce position sizes, increase caution
Risk Management Integration
Confidence-Based Sizing: Larger positions for higher confidence signals
Regime-Aware Stops: Wider stops in volatile regimes
Multi-Timeframe Confirmation: Align signals across timeframes
Volume Confirmation: Require volume support for major signals
Originality and Innovation
This indicator represents genuine innovation in several areas:
Mathematical Approach
First application of Lorentzian geometry to market pattern recognition. Unlike Euclidean-based systems, this naturally handles market non-linearities.
Feature Engineering
Sophisticated multi-dimensional feature space combining price, volume, volatility, and momentum in normalized form.
Visualization System
Professional-grade dashboard system providing comprehensive market intelligence in intuitive format.
Performance Tracking
Real-time performance analytics typically found only in institutional trading systems.
Development Journey
Creating this indicator involved overcoming numerous technical challenges:
Mathematical Complexity: Translating theoretical concepts into practical code
Performance Optimization: Balancing accuracy with computational efficiency
User Interface Design: Making complex data accessible and actionable
Signal Quality: Filtering noise while maintaining responsiveness
The result is a tool that brings institutional-grade analytics to individual traders while maintaining the theoretical rigor of its mathematical foundation.
Best Practices
- Parameter Optimization
- Start with default settings and adjust based on:
Market Characteristics: Volatile vs. stable
Trading Timeframe: Scalping vs. swing trading
Risk Tolerance: Conservative vs. aggressive
Signal Confirmation
Never trade on Lorentzian signals alone:
Price Action: Confirm with support/resistance
Volume: Verify with volume analysis
Multiple Timeframes: Check higher timeframe alignment
Market Context: Consider overall market conditions
Risk Management
Position Sizing: Scale with confidence levels
Stop Losses: Adapt to market volatility
Profit Targets: Based on historical performance
Maximum Risk: Never exceed 2-3% per trade
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or guarantee profitable trading results. The Lorentzian classification system reveals market patterns but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
Market dynamics are inherently uncertain, and past performance does not guarantee future results. This tool should be used as part of a comprehensive trading strategy, not as a standalone solution.
Bringing the elegance of relativistic geometry to market analysis through sophisticated pattern recognition and intuitive visualization.
Thank you for sharing the idea. You're more than a follower, you're a leader!
@vasanthgautham1221
Trade with precision. Trade with insight.
— Dskyz , for DAFE Trading Systems
Risk Calculator PRO — manual lot size + auto lot-suggestionWhy risk management?
90 % of traders blow up because they size positions emotionally. This tool forces Risk-First Thinking: choose the amount you’re willing to lose, and the script reverse-engineers everything else.
Key features
1. Manual or Market Entry – click “Use current price” or type a custom entry.
2. Setup-based ₹-Risk – four presets (A/B/C/D). Edit to your workflow.
3. Lot-Size Input + Auto Lot Suggestion – you tell the contract size ⇒ script tells you how many lots.
4. Auto-SL (optional) – tick to push stop-loss to exactly 1-lot risk.
5. Instant Targets – 1 : 2, 1 : 3, 1 : 4, 1 : 5 plotted and alert-ready.
6. P&L Preview – table shows potential profit at each R-multiple plus real ₹ at SL.
7. Margin Column – enter per-lot margin once; script totals it for any size.
8. Clean Table UI – dark/light friendly; updates every 5 bars.
9. Alert Pack – SL, each target, plus copy-paste journal line on the chart.
How to use
1. Add to chart > “Format”.
2. Type the lot size for the symbol (e.g., 1250 for Natural Gas, 1 for cash equity).
3. Pick Side (Buy / Sell) & Setup grade.
4. ✅ If you want the script to place SL for you, tick Auto-SL (risk = 1 lot).
5. Otherwise type your own Stop-loss.
6. Read the table:
• Suggested lots = how many to trade so risk ≤ setup ₹.
• Risk (currency) = real money lost if SL hits.
7. Set TradingView alerts on the built-in conditions (T1_2, SL_hit, etc.) if you’d like push / email.
8. Copy the orange CSV label to Excel / Sheets for journalling.
Best practices
• Never raise risk to “fit” a trade. Lower size instead.
• Review win-rate vs. R multiple monthly; adjust setups A–D accordingly.
• Test Auto-SL in replay before going live.
Disclaimer
This script is educational. Past performance ≠ future results. The author isn’t responsible for trading losses.
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
OTE & A-B-C Zone Indicator SwiftEdgeOTE & A-B-C Zone Indicator SwiftEdge
Overview
The OTE & A-B-C Zone Indicator SwiftEdge is a versatile tool designed to help traders identify high-probability trading setups using a combination of Optimal Trade Entry (OTE) zones, Fibonacci levels, and A-B-C price patterns. This indicator is particularly useful for traders who rely on price action and Fibonacci-based strategies to find entry points, set stop-losses, and target potential take-profit levels. By integrating swing point detection, trend analysis, and Fibonacci projections, SwiftEdge provides a clear visual framework for making informed trading decisions across various timeframes.
What It Does
SwiftEdge identifies key price levels and zones to guide your trading:
OTE Zone: Highlights the Optimal Trade Entry zone between swing points A (swing high) and B (swing low) using Fibonacci retracement levels (default: 0.618 to 0.786). This zone represents a high-probability area for price reversals, making it an ideal entry point for trades.
A-B-C Pattern: Marks the latest swing points as A (swing high), B (swing low), and C (projected take-profit level) with dashed lines and labels. A solid line connects A to B to C, visually illustrating the price movement from entry to target.
Take-Profit Zones: Projects three customizable take-profit levels (TP1, TP2, TP3) based on Fibonacci extensions (default: 1.272, 1.618, 2.0) from the A-B swing, helping traders plan exits with favorable risk-reward ratios.
How It Works
SwiftEdge combines several technical components to create a cohesive trading system:
Swing Point Detection: Identifies significant swing highs (A) and swing lows (B) using a dynamic lookback period that adjusts to the selected timeframe. On lower timeframes like 1-minute charts, an ATR-based filter reduces noise by requiring price movements to exceed a threshold (0.5 * ATR(14)).
Trend Analysis: Uses an Exponential Moving Average (EMA) to determine the trend direction (default: 50-period EMA on 1H). The indicator marks uptrends (price above EMA) in green and downtrends (price below EMA) in red, ensuring trades align with the market's direction.
Fibonacci Levels: Applies Fibonacci retracement to define the OTE zone between A and B, and Fibonacci extensions to project take-profit levels (C) beyond the initial swing. This approach leverages the natural tendency of markets to respect Fibonacci ratios for reversals and extensions.
Visual Clarity: Displays only the latest A-B-C pattern with three dashed lines (A, B, C) and a solid connecting line, ensuring the chart remains uncluttered and easy to interpret.
The combination of these elements creates a structured setup where the OTE zone (between A and B) serves as an entry point, while the projected C level offers a target, all within the context of the prevailing trend. This synergy makes SwiftEdge a powerful tool for traders seeking to combine price action, trend analysis, and Fibonacci strategies.
How to Use
Add the Indicator: Apply the indicator to your chart via TradingView's indicator menu.
Identify the Trend: The OTE zone and A-B-C pattern will be colored green in uptrends (price above EMA) or red in downtrends (price below EMA). Use this to determine the market direction.
Entry Point: Look for price reversals within the OTE zone (between A and B). This zone is typically between the 0.618 and 0.786 Fibonacci retracement levels of the A-B swing, making it a high-probability area for entries.
Stop-Loss: Place your stop-loss below the OTE zone in an uptrend (or above in a downtrend) to protect against false breakouts.
Take-Profit Targets: Use the projected take-profit zones (TP1, TP2, TP3) as potential exit levels. These are based on Fibonacci extensions and can be toggled on/off in the settings.
Customization:
Adjust the Fibonacci levels for the OTE zone (Fibonacci Level 1 and Fibonacci Level 2) to suit your strategy.
Modify the take-profit levels (Fibonacci Extension Level for TP1/TP2/TP3) to target different extension ratios.
Change the lookback period (Base Lookback Period) and EMA period (Base EMA Period) to fine-tune swing point detection and trend sensitivity.
Customize colors for uptrends, downtrends, and A-B-C lines to match your preferences.
What Makes It Unique
SwiftEdge stands out by integrating swing point detection, Fibonacci-based OTE zones, and A-B-C price patterns into a single, visually intuitive indicator. Unlike standalone Fibonacci tools or trend indicators, SwiftEdge combines these elements to provide a complete trading setup: it identifies entry zones (OTE), confirms trend direction (EMA), and projects take-profit targets (Fibonacci extensions). The dynamic timeframe adjustment ensures consistent performance across all chart intervals, while the clean A-B-C visualization (with only the latest pattern displayed) prevents chart clutter, making it easier to focus on the most relevant price levels.
Notes
This indicator is designed for traders familiar with price action and Fibonacci strategies. It does not guarantee profits and should be used in conjunction with other analysis tools and proper risk management.
Performance may vary depending on market conditions and timeframe. Test the indicator on a demo account before using it in live trading.
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Momentum Volume Divergence (MVD) EnhancedMomentum Volume Divergence (MVD) Enhanced is a powerful indicator that detects price-momentum divergences and momentum suppression for reversal trading. Optimized for XRP on 1D charts, it features dynamic lookbacks, ATR-adjusted thresholds, and SMA confirmation. Signals include strong divergences (triangles) and suppression warnings (crosses). Includes a detailed user guide—try it out and share your feedback!
Setup: Add to XRP 1D chart with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA crossovers. See full guide for details!
Disclaimer: This indicator is for educational purposes only, not financial advice. Trading involves risk—use at your discretion.
Momentum Volume Divergence (MVD) Enhanced Indicator User Guide
Version: Pine Script v6
Designed for: TradingView
Recommended Use: XRP on 1-day (1D) chart
Date: March 18, 2025
Author: Herschel with assistance from Grok 3 (xAI)
Overview
The Momentum Volume Divergence (MVD) Enhanced indicator is a powerful tool for identifying price-momentum divergences and momentum suppression patterns on XRP’s 1-day (1D) chart. Plotted below the price chart, it provides clear visual signals to help traders spot potential reversals and trend shifts.
Purpose
Detect divergences between price and momentum for buy/sell opportunities.
Highlight momentum suppression as warnings of fading trends.
Offer actionable trading signals with intuitive markers.
Indicator Components
Main Plot
Volume-Weighted Momentum (vw_mom): Blue line showing momentum adjusted by volume.
Above 0 = bullish momentum.
Below 0 = bearish momentum.
Zero Line: Gray dashed line at 0, separating bullish/bearish zones.
Key Signals
Strong Bearish Divergence:
Marker: Red triangle at the top.
Meaning: Price makes a higher high, but momentum weakens, confirmed by a drop below the 5-day SMA.
Action: Potential sell/short signal.
Strong Bullish Divergence:
Marker: Green triangle at the bottom.
Meaning: Price makes a lower low, but momentum strengthens, confirmed by a rise above the 5-day SMA.
Action: Potential buy/long signal.
Bearish Suppression:
Marker: Orange cross at the top + red background.
Meaning: Strong bullish momentum with low volume in a volume downtrend, suggesting fading strength.
Action: Warning to avoid longs or exit early.
Bullish Suppression:
Marker: Yellow cross at the bottom + green background.
Meaning: Strong bearish momentum with low volume in a volume uptrend, suggesting fading weakness.
Action: Warning to avoid shorts or exit early.
Debug Plots (Optional)
Volume Ratio: Gray line (volume vs. its MA) vs. yellow line (threshold).
Momentum Threshold: Purple lines (positive/negative momentum cutoffs).
Smoothed Momentum: Orange line (raw momentum).
Confirmation SMA: Purple line (price trend confirmation).
Labels
Text labels (e.g., "Bear Div," "Bull Supp") mark detected patterns.
How to Use the Indicator
Step-by-Step Trading Process
1. Monitor the Chart
Load your XRP 1D chart with the indicator applied.
Observe the blue vw_mom line and signal markers.
2. Spot a Signal
Primary Signals: Look for red triangles (strong_bear) or green triangles (strong_bull).
Warnings: Note orange crosses (suppression_bear) or yellow crosses (suppression_bull).
3. Confirm the Signal
For Strong Bullish Divergence (Buy):
Green triangle appears.
Price closes above the 5-day SMA (purple line) and a recent swing high.
Optional: Volume ratio (gray line) exceeds the threshold (yellow line).
For Strong Bearish Divergence (Sell):
Red triangle appears.
Price closes below the 5-day SMA and a recent swing low.
Optional: Volume ratio (gray line) falls below the threshold (yellow line).
4. Enter the Trade
Long:
Buy at the close of the signal bar.
Stop loss: Below the recent swing low or 2 × ATR(14) below entry.
Short:
Sell/short at the close of the signal bar.
Stop loss: Above the recent swing high or 2 × ATR(14) above entry.
5. Manage the Trade
Take Profit:
Aim for a 2:1 or 3:1 risk-reward ratio (e.g., risk $0.05, target $0.10-$0.15).
Or exit when an opposite suppression signal appears (e.g., orange cross for longs).
Trailing Stop:
Move stop to breakeven after a 1:1 RR move.
Trail using the 5-day SMA or 2 × ATR(14).
Early Exit:
Exit if a suppression signal appears against your position (e.g., suppression_bull while short).
6. Filter Out Noise
Avoid trades if a suppression signal precedes a divergence within 2-3 days.
Optional: Add a 50-day SMA on the price chart:
Longs only if price > 50-SMA.
Shorts only if price < 50-SMA.
Example Trades (XRP 1D)
Bullish Trade
Signal: Green triangle (strong_bull) at $0.55.
Confirmation: Price closes above 5-SMA and $0.57 high.
Entry: Buy at $0.58.
Stop Loss: $0.53 (recent low).
Take Profit: $0.63 (2:1 RR) or exit on suppression_bear.
Outcome: Price hits $0.64, exit at $0.63 for profit.
Bearish Trade
Signal: Red triangle (strong_bear) at $0.70.
Confirmation: Price closes below 5-SMA and $0.68 low.
Entry: Short at $0.67.
Stop Loss: $0.71 (recent high).
Take Profit: $0.62 (2:1 RR) or exit on suppression_bull.
Outcome: Price drops to $0.61, exit at $0.62 for profit.
Tips for Success
Combine with Price Levels:
Use support/resistance zones (e.g., weekly pivots) to confirm entries.
Monitor Volume:
Rising volume (gray line above yellow) strengthens signals.
Adjust Sensitivity:
Too many signals? Increase div_strength_threshold to 0.7.
Too few signals? Decrease to 0.3.
Backtest:
Review 20-30 past signals on XRP 1D to assess performance.
Avoid Choppy Markets:
Skip signals during low volatility (tight price ranges).
Troubleshooting
No Signals:
Lower div_strength_threshold to 0.3 or mom_threshold_base to 0.2.
Check if XRP’s volatility is unusually low.
False Signals:
Increase sma_confirm_length to 7 or add a 50-SMA filter.
Indicator Not Loading:
Ensure the script compiles without errors.
Customization (Optional)
Change Colors: Edit color.* values (e.g., color.red to color.purple).
Add Alerts: Use TradingView’s alert menu for "Strong Bearish Divergence Confirmed," etc.
Test Other Assets: Experiment with BTC or ETH, adjusting inputs as needed.
Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion.
Setup: Use on XRP 1D with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA cross. Stop: 2x ATR(14). Profit: 2:1 RR or suppression exit. Full guide available separately!
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY TradingView technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on TradingView. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
TradingView Backtester Integration
Divergence IQ is fully compatible with the TradingView backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much TradingView community!
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
IU Opening range Breakout StrategyIU Opening Range Breakout Strategy
This Pine Script strategy is designed to capitalize on the breakout of the opening range, which is a popular trading approach. The strategy identifies the high and low prices of the opening session and takes trades based on price crossing these levels, with built-in risk management and trade limits for intraday trading.
Key Features:
1. Risk Management:
- Risk-to-Reward Ratio (RTR):
Set a customizable risk-to-reward ratio to calculate target prices based on stop-loss levels.
Default: 2:1
- Max Trades in a Day:
Specify the maximum number of trades allowed per day to avoid overtrading.
Default: 2 trades in a day.
- End-of-Day Close:
Automatically closes all open positions at a user-defined session end time to ensure no overnight exposure.
Default: 3:15 PM
2. Opening Range Identification
- Opening Range High and Low:
The script detects the high and low of the first trading session using Pine Script's session functions.
These levels are plotted as visual guides on the chart:
- High: Lime-colored circles.
- Low: Red-colored circles.
3. Trade Entry Logic
- Long Entry:
A long trade is triggered when the price closes above the opening range high.
- Entry condition: Crossover of the price above the opening range high.
-Short Entry:
A short trade is triggered when the price closes below the opening range low.
- Entry condition: Crossunder of the price below the opening range low.
Both entries are conditional on the absence of an existing position.
4. Stop Loss and Take Profit
- Long Position:
- Stop Loss: Previous candle's low.
- Take Profit: Calculated based on the RTR.
- **Short Position:**
- **Stop Loss:** Previous candle's high.
- **Take Profit:** Calculated based on the RTR.
The strategy plots these levels for visual reference:
- Stop Loss: Red dashed lines.
- Take Profit: Green dashed lines.
5. Visual Enhancements
-Trade Level Highlighting:
The script dynamically shades the areas between the entry price and SL/TP levels:
- Red shading for the stop-loss region.
- Green shading for the take-profit region.
- Entry Price Line:
A silver-colored line marks the average entry price for active trades.
How to Use:
1.Input Configuration:
Adjust the Risk-to-Reward ratio, max trades per day, and session end time to suit your trading preferences.
2.Visual Cues:
Use the opening range high/low lines and shading to identify potential breakout opportunities.
3.Execution:
The strategy will automatically enter and exit trades based on the conditions. Review the plotted SL and TP levels to monitor the risk-reward setup.
Important Notes:
- This strategy is designed for intraday trading and works best in markets with high volatility during the opening session.
- Backtest the strategy on your preferred market and timeframe to ensure compatibility.
- Proper risk management and position sizing are essential when using this strategy in live markets.
SiCInside Sweep Close (ISC):
This concept captures a specific price action behavior and can help refine trading strategies for better precision. Here's a detailed explanation:
Inside:
The closing price of the candle stays within the range of the previous candle.
This indicates a containment of price action, suggesting indecision or preparation for a significant move.
Sweep:
The wick of the candle takes out (or "sweeps") the low (or high) of the previous candle.
This sweep can trigger stop-losses of retail traders or activate pending orders, often used by smart money strategies.
Close:
The candle ultimately closes inside the range of the previous candle.
This close signifies that the sweep was a liquidity grab rather than a genuine breakout, providing an actionable trading signal.
How ISC Can Be Used in Trading:
Liquidity Grab Recognition:
ISC can indicate when liquidity is swept from the market, making it an ideal entry point for traders anticipating a reversal or continuation.
Smart Money Concept (SMC) Synergy:
If you follow SMC principles, ISC aligns with key concepts like liquidity sweeps, order blocks, and mitigation zones.
Risk Management:
By identifying the ISC setup, you can place tighter stop-loss levels just outside the sweep, optimizing risk-reward ratios.
Entry Signals:
When you spot an ISC, you can enter trades at the close of the candle, anticipating a move in the direction opposite to the sweep.
Example of ISC in Action:
Imagine a bearish candle:
The wick sweeps the low of the previous candle, possibly triggering stop-losses.
However, the close stays inside the previous candle’s range.
This setup might indicate a reversal, where price moves upward after grabbing liquidity.
Why This Name Works:
It’s concise, professional, and directly linked to the trading action you’re describing.
The short form, ISC, is easy to remember and discuss within trading circles or while teaching others.
It ties into widely known concepts like smart money, price action, and liquidity sweeps, making it relatable yet unique.
Does this align with how you envision using the concept? Let me know if you’d like more refinements or visual examples!
Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
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 CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. 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: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 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 2h 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 Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
30-Minute Candle Strategy30-Minute Candle Trading Strategy
This strategy works on a 30-minute candle timeframe. When a new 30-minute candle opens, the following actions will take place based on the previous 30-minute candle's closing price:
Buy Trade Setup:
If the market opens above the previous 30-minute candle's closing price, a buy trade will be executed immediately at the market price.
The stop-loss will be set at the previous 30-minute candle's closing price.
There will be no fixed target.
The trade will be closed 1 minute before the current 30-minute candle closes, regardless of profit or loss.
Sell Trade Setup:
If a buy trade hits the stop-loss and the market moves below the previous 30-minute candle's closing price, a sell trade will be executed immediately at the market price.
The stop-loss for the sell trade will also be set at the previous 30-minute candle's closing price.
There will be no fixed target.
The trade will be closed 1 minute before the current 30-minute candle closes, regardless of profit or loss.
Procedure:
This process will repeat for every 30-minute candle.
If the market crosses the previous 30-minute candle's closing price to the upside, a buy trade will be executed, and the stop-loss will be set at the previous candle's closing price.
If the market crosses the previous 30-minute candle's closing price to the downside, a sell trade will be executed, and the stop-loss will also be set at the previous candle's closing price.
Each trade will be closed 1 minute before the current candle closes.
Key Points:
This strategy applies to every new 30-minute candle.
The stop-loss will always be based on the previous 30-minute candle's closing price.
If a stop-loss is hit, the strategy will automatically switch to the opposite trade (buy to sell or sell to buy) based on market movement crossing the previous candle's closing price.
This is a repetitive and systematic approach to trading, ensuring the rules are followed for every 30-minute candle.
Marcel's Dynamic Profit / Loss Calculator for GoldOverview
This Dynamic Risk / Reward Tool for Gold is designed to help traders efficiently plan and manage their trades in the volatile gold market. This script provides a clear visualisation of trade levels (Entry, Stop Loss, Take Profit) while dynamically calculating potential profit and loss. It ensures gold traders can assess their positions with precision, saving time and improving risk management.
Key Features
1. Trade Level Visualisation:
Plots Entry (Blue), Stop Loss (Red), and Take Profit (Green) lines directly on the chart.
Helps you visualise and confirm trade setups quickly which is good for scalping and day trades.
2. Dynamic Risk and Reward Calculations:
Calculates potential profit and loss in real time based on user-defined inputs such as position size, leverage, and account equity.
Displays a summary panel showing risk/reward metrics directly on the chart.
3. Customisable Settings:
Allows you to adjust key parameters like account equity, position size, leverage, and specific price levels for Entry, Stop Loss, and Take Profit.
Defaults are dynamically generated for convenience but remain fully adjustable for flexibility.
How It Works
The script uses gold-specific conventions (e.g., 1 lot = 100 ounces, 1 pip = 0.01 price change) to calculate accurate risk and reward metrics.
It dynamically positions Stop Loss and Take Profit levels relative to the entry price, based on user-defined or default offsets.
A real-time summary panel is displayed in the bottom-right corner of the chart, showing:
Potential Profit: The monetary value if the Take Profit is hit.
Potential Lo
ss: The monetary value if the Stop Loss is hit.
How to Use It
1. Add the script to your chart on a gold trading pair (e.g., XAUUSD).
2. Input your:
Account equity.
Leverage.
Position size (in lots).
Desired En
try Price (default: current close price).
3. Adjust the Stop Loss and Take Profit levels to your strategy, or let the script use default offsets of:
500 pips below the Entry for Stop Loss.
1000 pips above the Entry for Take Profit.
4. Review the plotted levels and the summary panel to confirm your trade aligns with your risk/reward goals.
Why Use This Tool?
Clarity and Precision:
Provides clear trade visuals and financial metrics for confident decision-making.
Time-Saving:
Automates the calculations needed to evaluate trade risk and reward.
Improved Risk Management:
Ensures you never trade without knowing your exact potential loss and gain.
This script is particularly useful for both novice and experienced traders looking to enhance their risk management and trading discipline in the Gold market. Enjoy clearer trades at speed.
Unlock the Power of Seasonality: Monthly Performance StrategyThe Monthly Performance Strategy leverages the power of seasonality—those cyclical patterns that emerge in financial markets at specific times of the year. From tax deadlines to industry-specific events and global holidays, historical data shows that certain months can offer strong opportunities for trading. This strategy was designed to help traders capture those opportunities and take advantage of recurring market patterns through an automated and highly customizable approach.
The Inspiration Behind the Strategy:
This strategy began with the idea that market performance is often influenced by seasonal factors. Historically, certain months outperform others due to a variety of reasons, like earnings reports, holiday shopping, or fiscal year-end events. By identifying these periods, traders can better time their market entries and exits, giving them an advantage over those who solely rely on technical indicators or news events.
The Monthly Performance Strategy was built to take this concept and automate it. Instead of manually analyzing market data for each month, this strategy enables you to select which months you want to focus on and then executes trades based on predefined rules, saving you time and optimizing the performance of your trades.
Key Features:
Customizable Month Selection: The strategy allows traders to choose specific months to test or trade on. You can select any combination of months—for example, January, July, and December—to focus on based on historical trends. Whether you’re targeting the historically strong months like December (often driven by the 'Santa Rally') or analyzing quieter months for low volatility trades, this strategy gives you full control.
Automated Monthly Entries and Exits: The strategy automatically enters a long position on the first day of your selected month(s) and exits the trade at the beginning of the next month. This makes it perfect for traders who want to benefit from seasonal patterns without manually monitoring the market. It ensures precision in entering and exiting trades based on pre-set timeframes.
Re-entry on Stop Loss or Take Profit: One of the standout features of this strategy is its ability to re-enter a trade if a position hits the stop loss (SL) or take profit (TP) level during the selected month. If your trade reaches either a SL or TP before the month ends, the strategy will automatically re-enter a new trade the next trading day. This feature ensures that you capture multiple trading opportunities within the same month, instead of exiting entirely after a successful or unsuccessful trade. Essentially, it keeps your capital working for you throughout the entire month, not just when conditions align perfectly at the beginning.
Built-in Risk Management: Risk management is a vital part of this strategy. It incorporates an Average True Range (ATR)-based stop loss and take profit system. The ATR helps set dynamic levels based on the market’s volatility, ensuring that your stops and targets adjust to changing market conditions. This not only helps limit potential losses but also maximizes profit potential by adapting to market behavior.
Historical Performance Testing: You can backtest this strategy on any period by setting the start year. This allows traders to analyze past market data and optimize their strategy based on historical performance. You can fine-tune which months to trade based on years of data, helping you identify trends and patterns that provide the best trading results.
Versatility Across Asset Classes: While this strategy can be particularly effective for stock market indices and sector rotation, it’s versatile enough to apply to other asset classes like forex, commodities, and even cryptocurrencies. Each asset class may exhibit different seasonal behaviors, allowing you to explore opportunities across various markets with this strategy.
How It Works:
The trader selects which months to test or trade, for example, January, April, and October.
The strategy will automatically open a long position on the first trading day of each selected month.
If the trade hits either the take profit or stop loss within the month, the strategy will close the current position and re-enter a new trade on the next trading day, provided the month has not yet ended. This ensures that the strategy continues to capture any potential gains throughout the month, rather than stopping after one successful trade.
At the start of the next month, the position is closed, and if the next month is also selected, a new trade is initiated following the same process.
Risk Management and Dynamic Adjustments:
Incorporating risk management with this strategy is as easy as turning on the ATR-based system. The strategy will automatically calculate stop loss and take profit levels based on the market’s current volatility, adjusting dynamically to the conditions. This ensures that the risk is controlled while allowing for flexibility in capturing profits during both high and low volatility periods.
Maximizing the Seasonal Edge:
By automating entries and exits based on specific months and combining that with dynamic risk management, the Ultimate Monthly Performance Strategy takes advantage of seasonal patterns without requiring constant monitoring. The added re-entry feature after hitting a stop loss or take profit ensures that you are always in the game, maximizing your chances to capture profitable trades during favorable seasonal periods.
Who Can Benefit from This Strategy?
This strategy is perfect for traders who:
Want to exploit the predictable, recurring patterns that occur during specific months of the year.
Prefer a hands-off, automated trading approach that allows them to focus on other aspects of their portfolio or life.
Seek to manage risk effectively with ATR-based stop losses and take profits that adjust to market conditions.
Appreciate the ability to re-enter trades when a take profit or stop loss is hit within the month, ensuring that they don't miss out on multiple opportunities during a favorable period.
In summary, the Ultimate Monthly Performance Strategy provides traders with a comprehensive tool to capitalize on seasonal trends, optimize their trading opportunities throughout the year, and manage risk effectively. The built-in re-entry system ensures you continue to benefit from the market even after hitting targets within the same month, making it a robust strategy for traders looking to maximize their edge in any market.
Risk Disclaimer:
Trading financial markets involves significant risk and may not be suitable for all investors. The Monthly Performance Strategy is designed to help traders identify seasonal trends, but past performance does not guarantee future results. It is important to carefully consider your risk tolerance, financial situation, and trading goals before using any strategy. Always use appropriate risk management and consult with a professional financial advisor if necessary. The use of this strategy does not eliminate the risk of losses, and traders should be prepared for the possibility of losing their entire investment. Be sure to test the strategy on a demo account before applying it in live markets.
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. 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: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 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 between 30 min and 4 hours and chart (optimal performance observed on 45 min 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 Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
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 CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. 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: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 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 2h 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 Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Simple Fibonacci Retracement Strategy This strategy uses Fibonacci retracement to identify key levels in the market and helps traders find good entry and exit points. By understanding and using this strategy, traders can improve their trading decisions and increase their chances of success in the market.
This strategy, called the "Simple Fibonacci Retracement Strategy," is designed to help traders identify potential entry and exit points in the market based on Fibonacci retracement levels. The code is written in Pine Script and runs on the TradingView platform.
Overall Function
The strategy uses Fibonacci retracement levels to identify potential support and resistance levels in the market. This helps traders find good entry and exit points for trades, as well as set stop-loss and take-profit levels to minimize risk and maximize gains.
Main Components of the Code
1. Input Parameters
Lookback Period: The number of bars used to identify the highest high and lowest low.
Fibonacci Direction: The choice of whether Fibonacci levels are calculated from top to bottom or bottom to top.
Fibonacci Levels: Specific Fibonacci levels (23.6%, 38.2%, 50%, 61.8%) used to identify important price levels.
Take Profit and Stop Loss: The number of pips used to set take profit and stop loss levels.
2. Identification of Highest and Lowest Points
The code uses the lookback period to find the highest high (highestHigh) and the lowest low (lowestLow). These levels form the basis for calculating the Fibonacci levels.
3. Calculation of Fibonacci Levels
Based on the direction chosen by the user, the code calculates the various Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 100%).
4. Trading Logic
Long Signal: Generated when the price crosses above the 61.8% Fibonacci level from bottom to top.
Short Signal: Generated when the price crosses below the 38.2% Fibonacci level from top to bottom.
When a long or short signal is generated, the strategy opens a position and sets take profit and stop loss levels based on the input parameters.
5. Visualization
The strategy plots the Fibonacci levels on the chart to provide a visual representation of the calculated levels. This helps traders see where the levels are in relation to the current price.
6. Alerts
The code also has functionality to create alerts (commented out), which can notify traders of buy or sell signals.
How to Use the Strategy
Configure Parameters: Adjust the lookback period, Fibonacci direction, and levels for take profit and stop loss to your preferences.
View the Chart: The Fibonacci levels will be plotted on the chart, providing a visual overview of potential support and resistance levels.
Trade Signals: Follow the generated buy and sell signals. Set your parameters in settings and adjust according to the generated buy and sell signals in the strategy tester. The strategy will automatically set your take profit and stop loss levels.
Evaluation and Adjustment: Monitor the performance of the strategy and make adjustments as needed to optimize the results.
Norwegian
Denne strategien, kalt "Simple Fibonacci Retracement Strategy", er designet for å hjelpe tradere med å identifisere mulige inngangs- og utgangspunkter i markedet basert på Fibonacci-retracementnivåer. Koden er skrevet i Pine Script og kjøres på TradingView-plattformen.
Overordnet Funksjon
Strategien bruker Fibonacci-retracementnivåer for å identifisere potensielle støtte- og motstandsnivåer i markedet. Dette hjelper tradere med å finne gode inngangs- og utgangspunkter for handler, samt å sette stop-loss og take-profit nivåer for å minimere risiko og maksimere gevinster.
Hovedkomponenter i Koden
1. Input Parametere
Lookback Period: Antall barer som brukes til å identifisere høyeste høydepunkt og laveste lavpunkt.
Fibonacci Direction: Valg om Fibonacci-nivåene skal beregnes fra topp til bunn eller bunn til topp.
Fibonacci Levels: Spesifikke Fibonacci-nivåer (23.6%, 38.2%, 50%, 61.8%) som brukes til å identifisere viktige prisnivåer.
Take Profit og Stop Loss: Antall pips som brukes til å sette take profit og stop loss nivåer.
2. Identifikasjon av Høyeste og Laveste Punkt
Koden bruker lookback perioden for å finne det høyeste høydepunktet (highestHigh) og det laveste lavpunktet (lowestLow). Disse nivåene er grunnlaget for å beregne Fibonacci-nivåene.
3. Beregning av Fibonacci-nivåer
Basert på retningen valgt av brukeren, beregner koden de forskjellige Fibonacci-nivåene (0%, 23.6%, 38.2%, 50%, 61.8%, 100%).
4. Handelslogikk
Long Signal: Genereres når prisen krysser over 61.8% Fibonacci-nivået fra bunn til topp.
Short Signal: Genereres når prisen krysser under 38.2% Fibonacci-nivået fra topp til bunn.
Når et long eller short signal genereres, åpner strategien en posisjon og setter take profit og stop loss nivåer basert på inputparametrene.
5. Visualisering
Strategien plottet Fibonacci-nivåene på chartet for å gi en visuell representasjon av de beregnede nivåene. Dette hjelper tradere med å se hvor nivåene er i forhold til den nåværende prisen.
6. Varsler
Koden har også funksjonalitet for å lage varsler (kommentert ut), som kan varsle tradere om kjøps- eller salgssignaler.
Slik Bruker Du Strategien
Konfigurer Parametere: Juster lookback perioden, Fibonacci-retningen, og nivåene for take profit og stop loss til dine preferanser.
Se på Chartet: Fibonacci-nivåene vil bli plottet på chartet, noe som gir deg en visuell oversikt over potensielle støtte- og motstandsnivåer.
Handle Signaler: Sett dine parametere i innstillinger og juster etter genererte kjøps- og salgssignalene i strategy testeren. Strategien vil automatisk sette dine take profit og stop loss nivåer.
Evaluering og Justering: Overvåk ytelsen til strategien og gjør justeringer etter behov for å optimalisere resultatene.
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. 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: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 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 4h 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 Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
CCI and MACD Auto Trading Strategy with Risk/RewardOverview:
This strategy combines the Commodity Channel Index (CCI) and the Moving Average Convergence Divergence (MACD) indicators to automate trading decisions. It dynamically sets stop-loss and take-profit levels based on recent lows and highs, ensuring a risk/reward ratio of 1:1.5. This script aims to leverage trend and momentum signals while maintaining effective risk management.
Originality and Usefulness:
This script is not just a simple mashup of CCI and MACD indicators; it incorporates dynamic risk management by setting stop-loss and take-profit levels based on recent price action. This approach helps traders to:
・Identify potential trend reversals using the combination of CCI and MACD signals.
・Manage trades effectively by setting realistic stop-loss and take-profit levels based on recent market data.
・Maintain a balanced risk/reward ratio, which is essential for sustainable trading.
Indicators Used:
・CCI (Commodity Channel Index):
・Measures the deviation of the price from its average over a specified period, typically ranging from -100 to +100.
・Helps identify overbought and oversold conditions.
・MACD (Moving Average Convergence Divergence):
・Utilizes the difference between short-term and long-term moving averages to indicate trend strength and direction.
・Provides momentum signals that can be used for timing entries and exits.
How It Works:
Entry Conditions:
Long Entry:
・The MACD histogram is above zero.
・The CCI crosses above the -100 line.
Short Entry:
・The MACD histogram is below zero.
・The CCI crosses below the +100 line.
Exit Conditions:
Long Positions:
・The stop-loss is set at the recent low.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Short Positions:
・The stop-loss is set at the recent high.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Risk Management:
・The script dynamically adjusts stop-loss and take-profit levels based on recent market data, ensuring that the risk/reward ratio is maintained at 1:1.5.
・This approach helps in managing the risk effectively while aiming for consistent profits.
Strategy Properties:
・Account Size: Configured for a realistic account size suitable for the average trader.
・Commission and Slippage: Includes settings for realistic commission and slippage to reflect real market conditions.
・Risk per Trade: Designed to risk no more than 5-10% of equity per trade, aligning with sustainable trading practices.
・Backtesting Results: Configured to generate a sufficient sample size (ideally more than 100 trades) for reliable backtesting results.
Revised Backtesting Settings
Ensure that your backtesting settings are realistic:
・Account Size: Set a realistic initial capital suitable for the average trader.
・Commission and Slippage: Include realistic commission fees and slippage.
・Risk Management: Ensure that each trade risks no more than 5-10% of the account equity.
・Sufficient Sample Size: Choose a dataset that will generate more than 100 trades to provide a robust sample size.
