Buy The Dip - ENGThis script implements a grid trading strategy for long positions in the USDT market. The core idea is to place a series of buy limit orders at progressively lower prices below an initial entry point, aiming to lower the average entry price as the price drops. It then aims to exit the entire position when the price rises a certain percentage above the average entry price.
Here's a detailed breakdown:
1. Strategy Setup (`strategy` function):
`'거미줄 자동매매 250227'`: The name of the strategy.
`overlay = true`: Draws plots and labels directly on the main price chart.
`pyramiding = 15`: Allows up to 15 entries in the same direction (long). This is essential for grid trading, as it needs to open multiple buy orders.
`initial_capital = 600`: Sets the starting capital for backtesting to 600 USDT.
`currency = currency.USDT`: Specifies the account currency as USDT.
`margin_long/short = 0`: Doesn't define specific margin requirements (might imply spot trading logic or rely on exchange defaults if used live).
`calc_on_order_fills = false`: Strategy calculations happen on each bar's close, not just when orders fill.
2. Inputs (`input`):
Core Settings:
`lev`: Leverage (default 10x). Used to calculate position sizes.
`Investment Percentage %`: Percentage of total capital to allocate to the initial grid (default 80%).
`final entry Percentage %`: Percentage of the *remaining* capital (100 - `Investment Percentage %`) to use for the "semifinal" entry (default 50%). The rest goes to the "final" entry.
`Price Adjustment Length`: Lookback period (default 4 bars) to determine the initial `maxPrice`.
`price range`: The total percentage range downwards from `maxPrice` where the grid orders will be placed (default -10%, meaning 10% down).
`tp`: Take profit percentage above the average entry price (default 0.45%).
`semifinal entry price percent`: Percentage drop from `maxPrice` to trigger the "semifinal" larger entry (default -12%).
`final entry price percent`: Percentage drop from `maxPrice` to trigger the "final" larger entry (default -15%).
Rounding & Display:
`roundprice`, `round`: Decimal places for rounding price and quantity calculations.
`texts`, `label_style`: User interface preferences for text size and label appearance on the chart.
Time Filter:
`startTime`, `endTime`: Defines the date range for the backtest.
3. Calculations & Grid Setup:
`maxPrice`: The highest price point for the grid setup. Calculated as the lowest low of the previous `len` bars only if no trades are open. If trades are open, it uses the entry price of the very first order placed in the current sequence (`strategy.opentrades.entry_price(0)`).
`minPrice`: The lowest price point for the grid, calculated based on `maxPrice` and `range1`.
`totalCapital`: The amount of capital (considering leverage and `per1`) allocated for the main grid orders.
`coinRatios`: An array ` `. This defines the *relative* size ratio for each of the 11 grid orders. Later orders (at lower prices) will be progressively larger.
`totalRatio`: The sum of all ratios (66).
`positionSizes`: An array calculated based on `totalCapital` and `coinRatios`. It determines the actual quantity (size) for each of the 11 grid orders.
4. Order Placement Logic (`strategy.entry`):
Initial Grid Orders:
Runs only if within the specified time range and no position is currently open (`strategy.opentrades == 0`).
A loop places 11 limit buy orders (`Buy 1` to `Buy 11`).
Prices are calculated linearly between `maxPrice` and `minPrice`.
Order sizes are taken from the `positionSizes` array.
Semifinal & Final Entries:
Two additional, larger limit buy orders are placed simultaneously with the grid orders:
`semifinal entry`: At `maxPrice * (1 - semifinal / 100)`. Size is based on `per2`% of the capital *not* used by the main grid (`1 - per1`).
`final entry`: At `maxPrice * (1 - final / 100)`. Size is based on the remaining capital (`1 - per2`% of the unused portion).
5. Visualization (`line.new`, `label.new`, `plot`, `plotshape`, `plotchar`):
Grid Lines & Labels:
When a position is open (`strategy.opentrades > 0`), horizontal lines and labels are drawn for each of the 11 grid order prices and the "final" entry price.
Lines extend from the bar where the *first* entry occurred.
Labels show the price and planned size for each level.
Dynamic Coloring: If the price drops below a grid level, the corresponding line turns green, and the label color changes, visually indicating that the level has been reached or filled.
Plotted Lines:
`maxPrice` (initial high point for the grid).
`strategy.position_avg_price` (current average entry price of the open position, shown in red).
Target Profit Price (`strategy.position_avg_price * (1 + tp / 100)`, shown in green).
Markers:
A flag marks the `startTime`.
A rocket icon (`🚀`) appears below the bar where the `final entry` triggers.
A stop icon (`🛑`) appears below the bar where the `semifinal entry` triggers.
6. Exit Logic (`strategy.exit`, `strategy.entry` with `qty=0`):
Main Take Profit (`Full Exit`):
Uses `strategy.entry('Full Exit', strategy.short, qty = 0, limit = target2)`. This places a limit order to close the entire position (`qty=0`) at the calculated take profit level (`target2 = avgPrice * (1 + tp / 100)`). Note: Using `strategy.entry` with `strategy.short` and `qty=0` is a way to close a long position, though `strategy.exit` is often clearer. This exit seems intended to apply whenever any part of the grid position is open.
First Order Trailing Stop (`1st order Full Exit`):
Conditional: Only active if `trail` input is true AND the *last* order filled was "Buy 1" (meaning only the very first grid level was entered).
Uses `strategy.exit` with `trail_points` and `trail_offset` based on ATR values to implement a trailing stop loss/profit mechanism for this specific scenario.
This trailing stop order is cancelled (`strategy.cancel`) if any subsequent grid orders ("Buy 2", etc.) are filled.
Final/Semifinal Take Profit (`final Full Exit`):
Conditional: Only active if more than 11 entries have occurred (meaning either the "semifinal" or "final" entry must have triggered).
Uses `strategy.exit` to place a limit order to close the entire position at the take profit level (`target3 = avgPrice * (1 + tp / 100)`).
7. Information Display (Tables & UI Label):
`statsTable` (Top Right):
A comprehensive table displaying grouped information:
Market Info (Entry Point, Current Price)
Position Info (Avg Price, Target Price, Unrealized PNL $, Unrealized PNL %, Position Size, Position Value)
Strategy Performance (Realized PNL $, Realized PNL %, Initial/Total Balance, MDD, APY, Daily Profit %)
Trade Statistics (Trade Count, Wins/Losses, Win Rate, Cumulative Profit)
`buyAvgTable` (Bottom Left):
* Shows the *theoretical* entry price and average position price if trades were filled sequentially up to each `buy` level (buy1 to buy10). It uses hardcoded percentage drops (`buyper`, `avgper`) based on the initial `maxPrice` and `coinRatios`, not the dynamically changing actual average price.
`uiLabel` (Floating Label on Last Bar):
Updates only on the most recent bar (`barstate.islast`).
Provides real-time context when a position is open: Size, Avg Price, Current Price, Open PNL ($ and %), estimated % drop needed for the *next* theoretical buy (based on `ui_gridStep` input), % rise needed to hit TP, and estimated USDT profit at TP.
Shows "No Position" and basic balance/trade info otherwise.
In Summary:
This is a sophisticated long-only grid trading strategy. It aims to:
1. Define an entry range based on recent lows (`maxPrice`).
2. Place 11 scaled-in limit buy orders within a percentage range below `maxPrice`.
3. Place two additional, larger buy orders at deeper percentage drops (`semifinal`, `final`).
4. Calculate the average entry price as orders fill.
5. Exit the entire position for a small take profit (`tp`) above the average entry price.
6. Offer a conditional ATR trailing stop if only the first order fills.
7. Provide extensive visual feedback through lines, labels, icons, and detailed information tables/UI elements.
Keep in mind that grid strategies can perform well in ranging or slowly trending markets but can incur significant drawdowns if the price trends strongly against the position without sufficient retracements to hit the take profit. The leverage (`lev`) input significantly amplifies both potential profits and losses.
Cerca negli script per "stop loss"
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
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.
1h Liquidity Swings Strategy with 1:2 RRLuxAlgo Liquidity Swings (Simulated):
Uses ta.pivothigh and ta.pivotlow to detect 1h swing highs (resistance) and swing lows (support).
The lookback parameter (default 5) controls swing point sensitivity.
Entry Logic:
Long: Uptrend, price crosses above 1h swing low (ta.crossover(low, support1h)), and price is below recent swing high (close < resistance1h).
Short: Downtrend, price crosses below 1h swing high (ta.crossunder(high, resistance1h)), and price is above recent swing low (close > support1h).
Take Profit (1:2 Risk-Reward):
Risk:
Long: risk = entryPrice - initialStopLoss.
Short: risk = initialStopLoss - entryPrice.
Take-profit price:
Long: takeProfitPrice = entryPrice + 2 * risk.
Short: takeProfitPrice = entryPrice - 2 * risk.
Set via strategy.exit’s limit parameter.
Stop-Loss:
Initial Stop-Loss:
Long: slLong = support1h * (1 - stopLossBuffer / 100).
Short: slShort = resistance1h * (1 + stopLossBuffer / 100).
Breakout Stop-Loss:
Long: close < support1h.
Short: close > resistance1h.
Managed via strategy.exit’s stop parameter.
Visualization:
Plots:
50-period SMA (trendMA, blue solid line).
1h resistance (resistance1h, red dashed line).
1h support (support1h, green dashed line).
Marks buy signals (green triangles below bars) and sell signals (red triangles above bars) using plotshape.
Usage Instructions
Add the Script:
Open TradingView’s Pine Editor, paste the code, and click “Add to Chart”.
Set Timeframe:
Use the 1-hour (1h) chart for intraday trading.
Adjust Parameters:
lookback: Swing high/low lookback period (default 5). Smaller values increase sensitivity; larger values reduce noise.
stopLossBuffer: Initial stop-loss buffer (default 0.5%).
maLength: Trend SMA period (default 50).
Backtesting:
Use the “Strategy Tester” to evaluate performance metrics (profit, win rate, drawdown).
Optimize parameters for your target market.
Notes on Limitations
LuxAlgo Liquidity Swings:
Simulated using ta.pivothigh and ta.pivotlow. LuxAlgo may include proprietary logic (e.g., volume or visit frequency filters), which requires the indicator’s code or settings for full integration.
Action: Please provide the Pine Script code or specific LuxAlgo settings if available.
Stop-Loss Breakout:
Uses closing price breakouts to reduce false signals. For more sensitive detection (e.g., high/low-based), I can modify the code upon request.
Market Suitability:
Ideal for high-liquidity markets (e.g., BTC/USD, EUR/USD). Choppy markets may cause false breakouts.
Action: Backtest in your target market to confirm suitability.
Fees:
Take-profit/stop-loss calculations exclude fees. Adjust for trading costs in live trading.
Swing Detection:
Swing high/low detection depends on market volatility. Optimize lookback for your market.
Verification
Tested in TradingView’s Pine Editor (@version=5):
plot function works without errors.
Entries occur strictly at 1h support (long) or resistance (short) in the trend direction.
Take-profit triggers at 1:2 risk-reward.
Stop-loss triggers on initial settings or 1h support/resistance breakouts.
Backtesting performs as expected.
Next Steps
Confirm Functionality:
Run the script and verify entries, take-profit (1:2), stop-loss, and trend filtering.
If issues occur (e.g., inaccurate signals, premature stop-loss), share backtest results or details.
LuxAlgo Liquidity Swings:
Provide the Pine Script code, settings, or logic details (e.g., volume filters) for LuxAlgo Liquidity Swings, and I’ll integrate them precisely.
Titan X 📈 Titan X – Optimized Trend Strategy with Gradient ZLEMA, RMI, CCI, ROC, and Volume Confirmation
Titan X is a precision-engineered trend-following strategy designed for crypto markets and high-volatility assets. It is not just a combination of indicators, but a carefully constructed, non-repainting system where each component plays a specific role in confirming high-probability trade setups. The strategy detects strong directional moves, confirms them with momentum and volume, and manages trade exits without relying on traditional stop losses.
🔍 How the Indicators Work Together
✅ 1. ZLEMA Baseline + Gradient Filter
A Zero Lag Exponential Moving Average (ZLEMA) is used to track directional trend with minimal lag.
A gradient (slope) is calculated from the ZLEMA to measure trend acceleration. This confirms whether a trend is gaining strength or losing momentum.
Entries are only taken when the ZLEMA gradient exceeds a user-defined threshold, ensuring trades are only taken in strong, developing trends.
✅ 2. RMI – Relative Momentum Index (with Memory)
RMI captures sustained momentum direction over time.
It helps validate that price isn't just spiking, but truly trending.
Titan X uses RMI as a trend memory filter, requiring consistent momentum alignment before entry.
✅ 3. Momentum Timing – ROC + CCI
The Rate of Change (ROC) determines the strength and direction of recent momentum.
The Commodity Channel Index (CCI) checks price deviation from a moving average baseline, identifying whether momentum is aligned with market structure.
This combo prevents trades in weak, flat, or conflicting conditions.
✅ 4. Volume Spike Confirmation
Titan X uses a relative volume filter, requiring the current bar’s volume to exceed a moving average threshold.
This ensures trades are only triggered when there is clear breakout interest from market participants, helping avoid fakeouts and low-volume moves.
🎯 Trade Entry & Exit Rules
✅ Entry Conditions:
All five filters must align:
Trend direction (ZLEMA slope)
Momentum (ROC & CCI)
Trend memory (RMI)
Volume (Spike filter)
Trades are entered on the next bar after all confirmations, ensuring 100% non-repainting behavior.
✅ Take Profit System (Multi-Level TP):
TP1: Closes 50% of the position at a user-defined % gain (default: 2%)
TP2: Closes the remaining 50% of the position at a higher % gain (default: 4%)
Each TP is executed via limit order to ensure realistic and backtestable fills.
❌ No Stop Loss Used
Instead of using fixed stop losses, Titan X closes positions early when trend conditions weaken.
This dynamic exit logic is based on a reversal in ZLEMA gradient, which serves as a weak trend detection system.
⏱️ Cooldown Logic
A 1-bar cooldown is enforced between trades to avoid same-bar exit/entry violations on TradingView.
This improves execution accuracy and avoids overtrading on choppy price action.
📊 Real-Time Strategy Dashboard
Titan X includes a live dashboard that provides full transparency:
Current Position (Long / Short / Flat)
Entry Price
TP1 Hit? / TP2 Hit?
Bars Since Entry
Win Rate (%)
Profit Factor
Ideal for both manual monitoring and automated bot strategies.
🔔 Bot-Ready Multi-Exchange Alerts
Alerts can be configured for:
ENTER-LONG, ENTER-SHORT
EXIT-LONG, EXIT-SHORT
TP1 / TP2 targets
Messages are fully customizable and designed for platforms like:
WonderTrading
3Commas
TradingConnector
⚙️ Designed For:
Timeframes: 1H and 4H (optimized for crypto)
Markets: Altcoins, BTC/ETH, high-volatility pairs
Traders: Trend-followers, momentum scalpers, algo bot users
Goal: High accuracy entries, structured exits, zero repainting, and flexible trade management
⚠️ TradingView Disclosure
This strategy is provided for educational purposes only. It does not constitute investment advice, nor does it guarantee any returns. Trading carries risk; test thoroughly before using in live environments.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
Profit Trailing BBandsProfit Trailing Trend BBands v4.7.5 with Double Trailing SL
A TradingView Pine Script Strategy
Created by Kevin Bourn and refined with the help of Grok 3 (xAI)
Overview
Welcome to Profit Trailing Trend BBands v4.7.5, a dynamic trading strategy designed to ride trends and lock in profits with a unique double trailing stop-loss mechanism. Built for TradingView’s Pine Script v6, this strategy combines Bollinger Bands for trend detection with a smart trailing system that doubles down on profit protection. Whether you’re trading XRP or any other asset, this tool aims to maximize gains while keeping risk in check—all with a clean, visual interface.
What It Does
Identifies Trends: Uses Bollinger Bands to spot uptrends (price crossing above the upper band) and downtrends (price crossing below the lower band).
Enters Positions: Opens long or short trades based on trend signals, with customizable position sizing and leverage.
Trails Profits: Employs a two-stage trailing stop-loss:
Initial Trailing SL: Acts as a take-profit level, set as a percentage (%) or dollar ($) distance from the entry price.
Tightened Trailing SL: Once the initial profit target is hit, the stop-loss tightens to half the initial distance, locking in gains as the trend continues.
Manages Risk: Includes a margin call feature to exit losing positions before they blow up your account.
Visualizes Everything: Plots Bollinger Bands (blue upper, orange lower) and a red stepped trailing stop-loss line for easy tracking.
Why Built It?
Captures Trends: Bollinger Bands are a proven way to catch momentum, and we tuned them for responsiveness (short length, moderate multiplier).
Secures Profits: Traditional trailing stops often leave money on the table or exit too early. The double trailing SL first takes a chunk of profit, then tightens up to ride the rest of the move.
Stays Flexible: Traders can tweak price sources, stop-loss types (% or $), and position sizing to fit their style.
Looks Good: Clear visuals help you see the strategy in action without cluttering your chart.
Originally refined for XRP, it’s versatile enough for most markets — crypto, forex, stocks, you name it.
How It Works
Core Components
Bollinger Bands:
Calculated using a simple moving average (SMA) and standard deviation.
Default settings: 6-period length, 1.66 multiplier.
Upper Band (blue): SMA + (1.66 × StdDev).
Lower Band (orange): SMA - (1.66 × StdDev).
Trend signals: Price crossing above the upper band triggers a long, below the lower band triggers a short.
Double Trailing Stop-Loss:
Initial SL: Set via "Trailing Stop-Loss Value" (default 6% or $6). Trails the price at this distance and doubles as the first profit target.
Tightened SL: Once price hits the initial SL distance in profit (e.g., +6%), the SL tightens to half (e.g., 3%) and continues trailing, locking in gains.
Visualized as a red stepped line, only visible during active positions.
Position Sizing:
Choose "% of Equity" (default 30%) or "Amount in $" to set trade size.
Leverage (default 10x) amplifies positions, capped by available equity to avoid overexposure.
Margin Call:
Exits positions if drawdown exceeds the "Margin %" (default 10%) to protect your account.
Backtesting Filter:
Starts trading after a user-defined date (default: Jan 1, 2020) for focused historical analysis.
Trade Logic
Long Entry: Price crosses above the upper Bollinger Band → Closes any short position, opens a long.
Short Entry: Price crosses below the lower Bollinger Band → Closes any long position, opens a short.
Exit: Position closes when price hits the trailing stop-loss or triggers a margin call.
How to Use It
Setup
Add to TradingView:
Open TradingView, go to the Pine Editor, paste the script, and click "Add to Chart."
Ensure you’re using Pine Script v6 (the script includes @version=6).
Configure Inputs:
Start Date for Backtesting: Set the date to begin historical testing (default: Jan 1, 2020).
BB Length & Mult: Adjust Bollinger Band sensitivity (default: 6, 1.66).
BB Price Source: Choose the price for BBands (default: Close).
Trend Price Source: Choose the price for trend detection (default: Close).
Trailing Stop-Loss Type: Pick "%" or "$" (default: Trailing SL %).
Trailing Stop-Loss Value: Set the initial SL distance (default: 6).
Margin %: Define the max drawdown before exit (default: 10%).
Order Size Type & Value: Set position size as % of equity (default: 30%) or $ amount.
Leverage: Adjust leverage (default: 10x).
Run It:
Use the Strategy Tester tab to backtest on your chosen asset and timeframe.
Watch the chart for blue/orange Bollinger Bands and the red trailing SL line.
Tips for Traders
Timeframes: Works on any timeframe, but test 1H or 4H for XRP—great balance of signals and noise.
Assets: Optimized for XRP, but tweak slValue and mult for other markets (e.g., tighter SL for low-volatility pairs).
Risk Management: Keep marginPercent low (5-10%) for volatile assets; adjust leverage based on your risk tolerance.
Visuals: The red stepped SL line shows only during trades—zoom in to see its tightening in action.
Visuals on the Chart
Blue Line: Upper Bollinger Band (trend entry for longs).
Orange Line: Lower Bollinger Band (trend entry for shorts).
Red Stepped Line: Trailing Stop-Loss (shifts tighter after the first profit target).
Order Labels: Short tags like "OL" (Open Long), "CS" (Close Short), "LSL" (Long Stop-Loss), etc., mark trades.
Disclaimer
Trading involves risk. This strategy is for educational and experimental use—backtest thoroughly and use at your own risk. Past performance doesn’t guarantee future results. Not financial advice—just a tool from traders, for traders.
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.
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.
ROBO STB GainCraft strategyPure Price Action Candlestick Strategy by ROBO STB
Overview
This strategy is built entirely on the principles of price action and candlestick analysis, designed for traders who prefer raw market data over traditional indicators. By focusing solely on candlestick patterns and their context within recent price movements, the strategy identifies high-probability entry and exit points in liquid markets.
Entry signals are generated based on these patterns appearing at significant market locations, such as after consolidations, pullbacks, or at key support/resistance levels.
Price Action Integration:
Instead of relying on oscillators or moving averages, the script leverages the inherent market structure provided by candlesticks to interpret potential trend reversals or continuations.
This approach provides a clearer view of market sentiment.
No External Indicators:
This script avoids the use of traditional indicators like RSI, MACD, or Bollinger Bands, offering a clean, uncluttered chart.
Risk Management (Optional):
Fixed-percentage risk management options can also be enabled, ensuring trades remain within acceptable risk parameters.
How the Strategy Works
Entry Conditions:
Buy Entry: A bullish candlestick pattern (e.g., bullish engulfing) forms after a period of consolidation or pullback, indicating potential upward momentum.
Sell Entry: A bearish candlestick pattern (e.g., bearish engulfing) suggests a downturn is likely.
Exit Conditions:
Exits are triggered by the appearance of reversal candlestick patterns or through predefined SL/TP levels.
The strategy adapts to varying market conditions by analyzing candlestick structures dynamically.
Ideal Use Cases
Short-Term Trading: Designed for day traders and scalpers targeting quick moves on shorter timeframes.
Highly Liquid Markets: Performs best in markets with high liquidity, such as Nifty, Bank Nifty, or major forex pairs, where candlestick patterns provide reliable signals.
30-Minute Timeframe: For optimal results, the strategy is recommended for use on a 30-minute timeframe.
Transparency and Realism
Backtesting Parameters:
The default backtesting settings simulate realistic trading conditions, including commissions and slippage, ensuring that results are not misleading.
Trade sizes are calibrated to risk sustainable amounts (.05% maximum equity per trade).
Dataset Selection:
This strategy has been tested on diverse datasets to produce a statistically significant number of trades, ensuring robust performance evaluation.
Why This Strategy is Unique
This script stands apart by offering a refined approach to price action trading. Unlike generic indicator mashups, it provides traders with an actionable, candlestick-focused methodology tailored for volatile, high-liquidity markets.
The strategy is both simple to understand and powerful in execution, making it an excellent tool for traders who want to develop their skills in raw price action analysis while maintaining strict risk management.
Key Features
Candlestick-Based Entry and Exit Signals:
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: 3:1
order size added -100
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.
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.
Please let me know if you have any doubts.
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.
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.
ICT Master Suite [Trading IQ]Hello Traders!
We’re excited to introduce the ICT Master Suite by TradingIQ, a new tool designed to bring together several ICT concepts and strategies in one place.
The Purpose Behind the ICT Master Suite
There are a few challenges traders often face when using ICT-related indicators:
Many available indicators focus on one or two ICT methods, which can limit traders who apply a broader range of ICT related techniques on their charts.
There aren't many indicators for ICT strategy models, and we couldn't find ICT indicators that allow for testing the strategy models and setting alerts.
Many ICT related concepts exist in the public domain as indicators, not strategies! This makes it difficult to verify that the ICT concept has some utility in the market you're trading and if it's worth trading - it's difficult to know if it's working!
Some users might not have enough chart space to apply numerous ICT related indicators, which can be restrictive for those wanting to use multiple ICT techniques simultaneously.
The ICT Master Suite is designed to offer a comprehensive option for traders who want to apply a variety of ICT methods. By combining several ICT techniques and strategy models into one indicator, it helps users maximize their chart space while accessing multiple tools in a single slot.
Additionally, the ICT Master Suite was developed as a strategy . This means users can backtest various ICT strategy models - including deep backtesting. A primary goal of this indicator is to let traders decide for themselves what markets to trade ICT concepts in and give them the capability to figure out if the strategy models are worth trading!
What Makes the ICT Master Suite Different
There are many ICT-related indicators available on TradingView, each offering valuable insights. What the ICT Master Suite aims to do is bring together a wider selection of these techniques into one tool. This includes both key ICT methods and strategy models, allowing traders to test and activate strategies all within one indicator.
Features
The ICT Master Suite offers:
Multiple ICT strategy models, including the 2022 Strategy Model and Unicorn Model, which can be built, tested, and used for live trading.
Calculation and display of key price areas like Breaker Blocks, Rejection Blocks, Order Blocks, Fair Value Gaps, Equal Levels, and more.
The ability to set alerts based on these ICT strategies and key price areas.
A comprehensive, yet practical, all-inclusive ICT indicator for traders.
Customizable Timeframe - Calculate ICT concepts on off-chart timeframes
Unicorn Strategy Model
2022 Strategy Model
Liquidity Raid Strategy Model
OTE (Optimal Trade Entry) Strategy Model
Silver Bullet Strategy Model
Order blocks
Breaker blocks
Rejection blocks
FVG
Strong highs and lows
Displacements
Liquidity sweeps
Power of 3
ICT Macros
HTF previous bar high and low
Break of Structure indications
Market Structure Shift indications
Equal highs and lows
Swings highs and swing lows
Fibonacci TPs and SLs
Swing level TPs and SLs
Previous day high and low TPs and SLs
And much more! An ongoing project!
How To Use
Many traders will already be familiar with the ICT related concepts listed above, and will find using the ICT Master Suite quite intuitive!
Despite this, let's go over the features of the tool in-depth and how to use the tool!
The image above shows the ICT Master Suite with almost all techniques activated.
ICT 2022 Strategy Model
The ICT Master suite provides the ability to test, set alerts for, and live trade the ICT 2022 Strategy Model.
The image above shows an example of a long position being entered following a complete setup for the 2022 ICT model.
A liquidity sweep occurs prior to an upside breakout. During the upside breakout the model looks for the FVG that is nearest 50% of the setup range. A limit order is placed at this FVG for entry.
The target entry percentage for the range is customizable in the settings. For instance, you can select to enter at an FVG nearest 33% of the range, 20%, 66%, etc.
The profit target for the model generally uses the highest high of the range (100%) for longs and the lowest low of the range (100%) for shorts. Stop losses are generally set at 0% of the range.
The image above shows the short model in action!
Whether you decide to follow the 2022 model diligently or not, you can still set alerts when the entry condition is met.
ICT Unicorn Model
The image above shows an example of a long position being entered following a complete setup for the ICT Unicorn model.
A lower swing low followed by a higher swing high precedes the overlap of an FVG and breaker block formed during the sequence.
During the upside breakout the model looks for an FVG and breaker block that formed during the sequence and overlap each other. A limit order is placed at the nearest overlap point to current price.
The profit target for this example trade is set at the swing high and the stop loss at the swing low. However, both the profit target and stop loss for this model are configurable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
For Longs, the selectable stop losses are:
Swing Low
Bottom of FVG or breaker block
The image above shows the short version of the Unicorn Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
For Shorts, the selectable stop losses are:
Swing High
Top of FVG or breaker block
The image above shows the profit target and stop loss options in the settings for the Unicorn Model.
Optimal Trade Entry (OTE) Model
The image above shows an example of a long position being entered following a complete setup for the OTE model.
Price retraces either 0.62, 0.705, or 0.79 of an upside move and a trade is entered.
The profit target for this example trade is set at the -0.5 fib level. This is also adjustable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
The image above shows the short version of the OTE Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
Liquidity Raid Model
The image above shows an example of a long position being entered following a complete setup for the Liquidity Raid Modell.
The user must define the session in the settings (for this example it is 13:30-16:00 NY time).
During the session, the indicator will calculate the session high and session low. Following a “raid” of either the session high or session low (after the session has completed) the script will look for an entry at a recently formed breaker block.
If the session high is raided the script will look for short entries at a bearish breaker block. If the session low is raided the script will look for long entries at a bullish breaker block.
For Longs, the profit target options are:
Swing high
User inputted Lib level
For Longs, the stop loss options are:
Swing low
User inputted Lib level
Breaker block bottom
The image above shows the short version of the Liquidity Raid Model in action!
For Shorts, the profit target options are:
Swing Low
User inputted Lib level
For Shorts, the stop loss options are:
Swing High
User inputted Lib level
Breaker block top
Silver Bullet Model
The image above shows an example of a long position being entered following a complete setup for the Silver Bullet Modell.
During the session, the indicator will determine the higher timeframe bias. If the higher timeframe bias is bullish the strategy will look to enter long at an FVG that forms during the session. If the higher timeframe bias is bearish the indicator will look to enter short at an FVG that forms during the session.
For Longs, the profit target options are:
Nearest Swing High Above Entry
Previous Day High
For Longs, the stop loss options are:
Nearest Swing Low
Previous Day Low
The image above shows the short version of the Silver Bullet Model in action!
For Shorts, the profit target options are:
Nearest Swing Low Below Entry
Previous Day Low
For Shorts, the stop loss options are:
Nearest Swing High
Previous Day High
Order blocks
The image above shows indicator identifying and labeling order blocks.
The color of the order blocks, and how many should be shown, are configurable in the settings!
Breaker Blocks
The image above shows indicator identifying and labeling order blocks.
The color of the breaker blocks, and how many should be shown, are configurable in the settings!
Rejection Blocks
The image above shows indicator identifying and labeling rejection blocks.
The color of the rejection blocks, and how many should be shown, are configurable in the settings!
Fair Value Gaps
The image above shows indicator identifying and labeling fair value gaps.
The color of the fair value gaps, and how many should be shown, are configurable in the settings!
Additionally, you can select to only show fair values gaps that form after a liquidity sweep. Doing so reduces "noisy" FVGs and focuses on identifying FVGs that form after a significant trading event.
The image above shows the feature enabled. A fair value gap that occurred after a liquidity sweep is shown.
Market Structure
The image above shows the ICT Master Suite calculating market structure shots and break of structures!
The color of MSS and BoS, and whether they should be displayed, are configurable in the settings.
Displacements
The images above show indicator identifying and labeling displacements.
The color of the displacements, and how many should be shown, are configurable in the settings!
Equal Price Points
The image above shows the indicator identifying and labeling equal highs and equal lows.
The color of the equal levels, and how many should be shown, are configurable in the settings!
Previous Custom TF High/Low
The image above shows the ICT Master Suite calculating the high and low price for a user-defined timeframe. In this case the previous day’s high and low are calculated.
To illustrate the customizable timeframe function, the image above shows the indicator calculating the previous 4 hour high and low.
Liquidity Sweeps
The image above shows the indicator identifying a liquidity sweep prior to an upside breakout.
The image above shows the indicator identifying a liquidity sweep prior to a downside breakout.
The color and aggressiveness of liquidity sweep identification are adjustable in the settings!
Power Of Three
The image above shows the indicator calculating Po3 for two user-defined higher timeframes!
Macros
The image above shows the ICT Master Suite identifying the ICT macros!
ICT Macros are only displayable on the 5 minute timeframe or less.
Strategy Performance Table
In addition to a full-fledged TradingView backtest for any of the ICT strategy models the indicator offers, a quick-and-easy strategy table exists for the indicator!
The image above shows the strategy performance table in action.
Keep in mind that, because the ICT Master Suite is a strategy script, you can perform fully automatic backtests, deep backtests, easily add commission and portfolio balance and look at pertinent metrics for the ICT strategies you are testing!
Lite Mode
Traders who want the cleanest chart possible can toggle on “Lite Mode”!
In Lite Mode, any neon or “glow” like effects are removed and key levels are marked as strict border boxes. You can also select to remove box borders if that’s what you prefer!
Settings Used For Backtest
For the displayed backtest, a starting balance of $1000 USD was used. A commission of 0.02%, slippage of 2 ticks, a verify price for limit orders of 2 ticks, and 5% of capital investment per order.
A commission of 0.02% was used due to the backtested asset being a perpetual future contract for a crypto currency. The highest commission (lowest-tier VIP) for maker orders on many exchanges is 0.02%. All entered positions take place as maker orders and so do profit target exits. Stop orders exist as stop-market orders.
A slippage of 2 ticks was used to simulate more realistic stop-market orders. A verify limit order settings of 2 ticks was also used. Even though BTCUSDT.P on Binance is liquid, we just want the backtest to be on the safe side. Additionally, the backtest traded 100+ trades over the period. The higher the sample size the better; however, this example test can serve as a starting point for traders interested in ICT concepts.
Community Assistance And Feedback
Given the complexity and idiosyncratic applications of ICT concepts amongst its proponents, the ICT Master Suite’s built-in strategies and level identification methods might not align with everyone's interpretation.
That said, the best we can do is precisely define ICT strategy rules and concepts to a repeatable process, test, and apply them! Whether or not an ICT strategy is trading precisely how you would trade it, seeing the model in action, taking trades, and with performance statistics is immensely helpful in assessing predictive utility.
If you think we missed something, you notice a bug, have an idea for strategy model improvement, please let us know! The ICT Master Suite is an ongoing project that will, ideally, be shaped by the community.
A big thank you to the @PineCoders for their Time Library!
Thank you!
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.
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.
Single Swing Strategy (SSS)Introduction
The Single Swing Strategy (SSS) is a trading strategy designed for assets that trend. It utilises a single technical indicator to identify potential buying opportunities in upward-trending markets. The strategy focuses on moments when the price of an asset breaks out to a new high, suggesting a strong upward momentum.
Components
1. Exponential Moving Averages (EMAs): SSS uses two EMAs to evaluate the overall asset trend. SSS describes an uptrend as identified, when the fast EMA crosses above the slow EMA and vice versa for a downtrend.
2. Breakout: The strategy validates the trend identified by the EMAs through breakouts in the price action of the asset over a specified lookback period. No indicator is required for this step.
3. Average Directional Index (ADX): The ADX is used to measure the strength of a trend. It does not indicate the trend's direction but rather its strength, whether it's an uptrend or downtrend. A high ADX value (typically above 25) suggests a strong trend, either up or down while a low ADX value (typically below 20) indicates a weak or non-trending market. The ADX itself is a moving average of the expanding range between the +DI and -DI.
4. Positive Directional Indicator (DI+): DI+ helps identify the presence and strength of uptrends. It is calculated based on the upward price movement between current and previous highs. A rising DI+ alongside a rising ADX suggests a strengthening uptrend. When DI+ crosses above DI-, it's often interpreted as a bullish signal.
5. Negative Directional Indicator (DI-): DI- is used to detect the presence and strength of downtrends.It is derived from the downward price movement between current and previous lows. An increasing DI- along with a rising ADX indicates a strengthening downtrend while a crossover of DI- above DI+ is typically seen as a bearish signal.
How it works
1. Regime filter with ADX, DI+, and DI-: The first step in taking a trade is to determine the direction of the trend using the +DI. If in an uptrend, the strategy checks if the ADX is above 25 to confirm a strong uptrend. -DI is not used since the strategy is long only. If in an uptrend and the trend is strong, trades can be opened.
2. Trend Identification with EMAs: Initially, the strategy uses two Exponential Moving Averages (fast and slow) to determine the asset trend. A fast EMA crossing above the slow EMA signifies an uptrend, and vice versa for a downtrend. This is the Entry signal to open a long position.
3. Trend Confirmation with Breakout: The strategy confirms the EMA-indicated trend through price breakouts over a specified lookback period. An EMA crossover without a price action breakout does not lead to an entry signal
4. Trade Management: After entering a trade, the strategy uses predefined levels for taking profit and setting stop losses. Trades are closed either when the price reaches the take-profit level or falls to the stop-loss level. Hence, risk management is built in.
Results
The backtest results can be found below. Initial capital of 10000 was used, this is a convenient amount for most retail traders, commission of $3 per order, position size of 3% of initial capital and slippage of 3 ticks. These are all representative of real world retail trading conditions.
Originality
The Single Swing Strategy (SSS)'s originality is in its blending of classical technical analysis; Trend Analysis through EMAs and Price Action through Breakout, into an innovative trading logic.
1. The Essence of Trend and Breakout in SSS
(i) Trend Recognition: At the heart of SSS is the Exponential Moving Averages (EMAs). While the use of EMAs is common, SSS employs them for trend analysis so an entry decision can be made. The strategy's core algorithm assesses the inception of an upward trend by observing a specific crossing pattern of the EMAs, a moment where the asset's momentum shifts, offering a strategic advantage.
(ii) Breakout Significance: The strategy's reliance on price breakouts isn't just about identifying a new high; it's about understanding market psychology. A breakout beyond a previous high signals not only momentum but also a collective market sentiment that favors upward movement. SSS attempts to capture this momentum, translating it into a tangible trading opportunity.
(iii)Strength of trend: The ADX and +DI double checks the trend is in the right direction and checks to see if the trend is strong enough hence, it prevents trading when the trend is not supportive.
2. Simplicity as a Cornerstone
(i) Clarity and Efficiency: In the realm of algorithmic trading, complexity isn't always synonymous with effectiveness. SSS' simplicity ensures its logic is transparent and its execution, efficient. This simplicity is a strategic choice, designed to reduce overfitting to past data and improve adaptability to real-market conditions.
(ii) Ease of Use and Decision Making: The straightforward nature of SSS may empower traders to make informed decisions without being overwhelmed by convoluted indicators. This is particularly useful because of the embedding of risk management using defined exit points after entry through a Take Profit and Stop Loss. This hardcodes a 3:1 risk reward ratio into every trade.
3. Positive Expectancy
(i) Performance Metrics: The SSS strategy shows its edge in its backtesting results. A 62% win rate, a profit factor of 1.7, profit ratio of 1.05 and an average trade gain of 4.7% are not just numbers; they show the mathematical edge over the backtest period, especially considering the high commissions and slippage factored into its design.
Trading
The SSS strategy has been backtested on the 1D timeframe of BTCUSD but users are encouraged to try it on other assets such as SPXL (5min), AAPL (5min) and others but the appropriate timeframe and trading costs may vary.
NOTE
Like any trading strategy, SSS does not guarantee profits. It's a tool to assist in decision-making, not a foolproof solution. Trading involves risks, particularly in volatile markets. Users should trade responsibly, considering their risk tolerance and financial situation. While SSS automates some aspects of trading, it requires continuous monitoring and does not replace the need for sound judgement and decision-making by the trader.
[SPOILED]SuperTrench - ETH Super ScalperHi Traders,
I'm republishing this script as I finally polished it to perfection IMO. The script uses 5 coding sections: entry, trend filter, pivot filter, take profit, and stop loss. The script mainly uses trailing as take profit; this is probably the easiest way to make a profitable scalper strategy.
Backtest capital is set to 1000 USDT, 35% equity, 0.04% commission, limited backtest date from Jan 2022 to now, backtested on ETH/USDT prep contracts 15m timeframe, result as shown below.
It looks unreal right? Hell no, I actually tested this strategy on Binance from Dec 06 to Dec 10. I got 8.29% return with 4x leverage, 50% equity setup; 75% win rate,1.58 profit factor, with 4.3% max drawdown, it is amazingly close to the backtest result.
User Manual
Entry >>> Stoch RSI:
I added 5 MA types to the Stoch RSI which is HMA/VWMA/WMA/EMA/SMA, HMA with Length setting of 5, 8 seems to be most efficient, VWMA and WMA with 8, 13 will generate less entry signals but with less entry risks.
Entry >>> R Style:
It based on price action, with candlestick makes a U turn, after 2nd candlestick confirmed, it generates entry signal, this will give you some extra entries, better leave it enabled.
Entry >>> Price Step:
This probably is the core feature of this strategy; also my secret ingredient to making this strategy this efficient. It is recommended to enable step 1-5, more steps basically means more entries, but they are not necessarily profitable.
Trend Filter >>> Price Step:
I couldn't tell you much details about how this indicator works, but it is a reliable indicator, based on price action, and I got some ideas from Demark9 indicator. The bigger the level, the stronger the filter is, please note that if 'Price Step Entries' less than Price Step Trend, entries will be ignored.
Pivot Filter >>> RSI Pivot & Pinbar Pivot:
RSI Pivot detects if the RSI signal line making U turn in certain condition, Pinbar detection combines R Style entry when price action U turn took place, these 2 pivot filter will close the trade once it is counter trend, so it better enable and leave it as is.
Trend Filter >>> Trend Magic:
Trend Magic uses CCI and ATR to calculate trend status, green means uptrend, red means downtrend, pretty straight forward, the best value for this indicator would be, 21, 34, 55, 89.
Trend Filter >>> Alpha:
This filter combines R style pivot, price step, EMA all together to detects consolidation area, because EMA was involved, so the best look back period would be around 15-35, it is best to use default value IMO, in another hands, if you need stronger filter, feel free to use 10, 18, 20, 25, 30, 35, make sure look back period should increase or decrease by 5 every time.
Take Profit and Stop Loss:
The default value for tp is set to 0.4%, but I also give you option to switch to ATR TP; you can adjust in the ATR multiplier, default ATR trailing stop loss uses 1 ATR, but you can adjust it for better drawdown tolerance. Fixed ATR SL is also given when fixed ATR is enabled. There will be a failsafe SL default set to 1% if price moves counter direction of opened position, it will close trade no matter what happens.
Enjoy :)
Mean reversal QFL v3My aim is to make the bots trade as you would trading QFL manually and “by the book” or at least to my experience and understanding from the material out there of how you should plan a QFL trade.
Im absolutely not a pro trader, I have made my share of costly mistakes trying to be clever or Beeing impatient resulting in painful losses. QFL is we’re I’ve had consistently good results tough.
Is this where I have to say I’m not a financial advisor and all that? Well I’m not. As always Do your own research and backtest, backtest, backtest.
First: I believe no bot strategy are set and forget, while they can run unattended 80-90% of the time you're always going to find yourself in a situation where you will have to manually handle a bad deal. It would also make sense to be somewhat involved in the really good trades making the most out of them. That’s why understanding the strategy the bot Is using is really important, hence why I prefer QFL. It's an easy concept to understand, and proved to be a safe way of making steady profit in pretty much all market conditions if done right.
Some changes in how aggressive you are might be needed if you are the impatient kind of trader who needs to see a lot of deals happening. But it is an added risk. In those cases Luc would advise to start “nibbling” but that would be hard to implement in a bot but I will see if that’s something I can implement.
Same goes for going the more conservative route when market conditions calls for it.
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
As a bit of a learning material i want to make a few points on important factors in trading using the QFL strategy:
• Identify strong bases
• Read the history of the chart
• No emotions
Trading QFL using a bot has it’s limitations:
· Some of the bases are questionable but im constantly trying to improve this
· The strategy don’t take into consideration chart history(success rate)*
· You need to follow a predefined (by you) buying ladder, hence not considering a particular coin's average price movement, which may vary quite a lot. This why I for now has limited the strategy to SIMPLE bots. So that unique alerts can be created for each pair.
· A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers(This is coming soon).
1. Some of the bases are questionable
The strategy will start trades of bases that you wouldn’t consider being a strong base(or a base at all) when looking at the chart.
For those not as familiar with QFL. What is a base, and what qualifies as a strong base?
• A base is also called the Support Level, which is the lowest price level that was reached before the price started turning and increasing again.
• A strong base is recognized by a steep fall in price after breaking the base(Panic), followed by a big reaction pump.
• The reaction pump is the most important factor to say that it is a strong base.
• And also the last base, the one you are trading of is the one that counts
Tip: Look for V shapes on the chart, easy to spot when zoomed out.
2. The integrated signals don’t take into consideration chart history(success rate)*
How can you assess the success rate by looking at the chart?
After finding the bases based on the criterias from the 1st point. Looking at the, how many times did it respect the base after breaking it? 7/10, 8/10, 9/10 times? Great! Chances of the next trade also respecting the base is big, and I would consider raising the TP on that deal. Any lower than that I would keep a really close eye on the deal, or even consider closing the deal. And again remember the last base is the one that counts. If all the others are nice strong bases but that last one you are about to take a trade off is no good the base is invalidated so be cautious.
3. You need to follow a predefined (by you) buying ladder
Crypto is volatile, and there is a huge variation in price movements on all the coins.
Trading manually, looking at the chart gives you a good idea on how much a coin on avg. drops below base, and how big the following reaction is. This gives you an indication on how deep you need to set your layers, and where you can take profit.
Using the strategy you have the backtester to see how much max deviation has been in the past so that you can figure out what the optimal max deviation is.
4. A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers.
Not going to say to much about this other than what I often do is:
When a bot has started a trade I usually take a look at the chart. If I like what I see, nice chart history, success rate and trading of a strong previous base etc, with the current base break resulting in a panic drop I will consider increasing the TP so that it will make more profit. This can be a bit risky but also very rewarding. Imagine filling all safeties and then selling just below base! Massive profits!! (Gotta be honest though, almost never stretch it that far with a bot though, but it is a possibility) .
If you have studied the chart and concluded that this particular trade has a 90% chance of success, there isn’t really any reason not to place TP just below base. This is where I would like to have the option of layering my sell orders as well so its something im working on implementing.
Trailing is an option in 3commas, but it’s slow to place orders making you miss a selling opportunity when the coin makes a sudden spike up.
ABOUT THIS STRATEGY
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
How to use:
- Add the script to the current chart
- Open the strategy settings
-Tweak the settings to to your liking.
-Make a SIMPLE bot in 3commas and use the same settings as you did in tradingview if you only want the strategy to send signals to open a deal and let 3commas handle the rest.
If you check safety orders, Take profit deal stop and Stop loss. The strategy will send all the orders to 3 commas. If that’s what you want set TP in 3commas to 50% set number of safety orders to 0 and keep stop loss unchecked.
- Insert bot details using the deal start condition message found in your 3commas bot.
- When happy, right click on the "..." next to the strategy name, then "Add alert'".
- Under "Condition", on the second line, chose "Any alert () function call". Add the webhook from 3commas( 3commas.io ), give it a name, use {{strategy.order.alert_message}} as a placeholder message and "create".
In the future this signal might make it to the 3commas marketplace. You can then subscribe to that signal where I have cherrypicked coins based on thorough backtesting and optimization.
How to obtain access to the script: send me a private message in Tradingview
Ultimate Strategy Shell [ArtK]This strategy shell script accepts entry/exit signals from an external study indicator.
It is built to cover most common trade execution strategies such as, multiple take profit levels, break even, trailing stop loss, position reverse, laddering and more.
It also aims to provide extended trade statistics such as the actual (win/loss) figures for trades instead of figures for orders as TradingView provides in the Strategy Test Overview.
Features
- 3 Take Profit levels.
- 3 Take Profit target type options (Percentage, Risk Reward Ratio or (IN DEVELOP) Strategy).
- 2 Stop Loss type options (Percentage, Strategy).
- Break Even stoop loss (will move the Stop Loss to the entry price after the 1st or 2nd Take Profit).
- Trailing Stop Loss (will move the Stop Loss after the last Take Profit at specified deviation on every candle).
- Trades Summary Label
Shows the number of wins and losses in a row.
Shows the actual (win/loss) figures for trades instead of figures for orders as TradingView provides in the Strategy Test Overview.
Shows the period from the first trade until the last trade.
Shows how many times each Take Profit level was reached (IN DEVELOP).
(IN DEVELOP) Shows the maximum Stop Loss when using the Stop Loss – Strategy option (helpful when estimating Stop Losses when leveraging).
Plots marks at the bottom of the chart to indicate winning or losing trades (helps to quickly find losing trades for example).
- Entry Filters
-- Date Time, allows placing trades only during the specified period.
-- ADX, filters trades below specified ADX value.
-- Max Stop Loss, can be enabled when the Stop Loss type is set to "Strategy". Used to prevent taking trades which exceed liquidation price.
-- Direction, will filter trades in a certain direction.
Instruction
- The strategy script relies on an external indicator therefore it is required to add the signal indicator first.
- To adapt the signal indicator to be compatible it must have only one plot.
-- The default value of the plot should be 1 when there is no buy/sell signal.
-- When the signal indicator signals BUY the line should plot the value
-- When the signal indicator signals SELL the line should plot the value
-- (I am aiming to support EXIT signals as well as the Stop Loss and Take Profit percentages in the near future)
- The first time you load the script it will show an error "Study Error: Signal source set to default ". This means the signal indicator was not selected.
The signal indicator should be selected in the strategy configuration panel option "Signal Source"
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.
