FU Candle Indicatorfu candle indicator for trading, it shows the direction in which the banks are trading
Графические паттерны
Enhanced Trend Following Strategy for DOGEUSDT (1-Min Chart)This strategy is designed to capitalize on trend momentum while minimizing risk through calculated entries and exits. With a focus on high-frequency trading, it leverages key technical indicators such as EMA crossovers, ADX trend strength, and RSI for market momentum analysis.
Performance Overview
Net Profit: +7,176.92 USDT (0.72%)
Total Closed Trades: 39
Win Rate: 76.92%
Profit Factor: 1.819
Max Drawdown: 3,600.01 USDT (0.36%)
Avg Trade: 184.02 USDT (0.18%)
Avg # Bars in Trades: 39
Key Features
Dual EMA Trend Confirmation:
A fast EMA (e.g., 50-period) and slow EMA (e.g., 200-period) identify strong trend directions and crossovers to confirm entry points.
ADX Trend Strength Filtering:
The Average Directional Index (ADX) helps ensure trades are only taken during strong trending conditions, avoiding choppy markets.
RSI Momentum Indicator:
Avoids overbought/oversold conditions by filtering entries when RSI is in favorable territory.
Multi-Timeframe Analysis:
Uses higher timeframe data to confirm trend direction, adding robustness to the strategy.
Risk Management:
Dynamic stop-loss and take-profit levels adjust based on market volatility to capture optimal profit potential.
Trade Logic
Long Entry:
When the fast EMA crosses above the slow EMA, ADX confirms a strong trend, and RSI indicates upward momentum.
Stop-loss set below recent swing low, take-profit at a 5-10% gain target.
Short Entry:
When the fast EMA crosses below the slow EMA, ADX confirms a downtrend, and RSI indicates downward momentum.
Stop-loss above recent swing high, take-profit at a 5-10% gain target.
Exit Conditions:
Take profit triggered when predefined levels are hit, or an opposite crossover occurs.
Stop loss triggered on price reversal beyond key support/resistance levels.
Potential Improvements
Fine-tuning ADX smoothing to reduce whipsaws.
Experimenting with dynamic position sizing based on ATR.
Adding volume-based confirmations for increased accuracy.
This strategy provides a solid foundation for trend-following traders, especially on shorter timeframes such as the 1-minute chart, with a strong focus on maintaining a high win rate and keeping drawdowns under control.
Give it a shot and optimize it further to suit your trading style!
DMI Strategy█ STRATEGY DESCRIPTION
The "DMI Strategy" is a trend-following strategy that uses the Directional Movement Index (DMI) and a 200-period Exponential Moving Average (EMA) to identify potential long entries. It enters a long position when specific conditions are met and exits when the Relative Strength Index (RSI) indicates overbought conditions. This strategy is designed for use on daily or higher timeframes.
█ WHAT IS THE DMI?
The Directional Movement Index (DMI) consists of three components:
- **DI+ (Plus Directional Indicator)**: Measures upward trend strength.
- **DI- (Minus Directional Indicator)**: Measures downward trend strength.
- **ADX (Average Directional Index)**: Measures overall trend strength, regardless of direction.
In this strategy, only the DI+ and DI- components are used to identify potential entry signals.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The DI+ value is less than 5, indicating weak upward momentum.
The close price is above the 200-period EMA, confirming a bullish trend.
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the 2-period RSI exceeds 65, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
DI Length: The lookback period for calculating the DMI components. Default is 3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for trending markets and performs best when the price is above the 200-period EMA.
It is sensitive to overbought conditions, as indicated by the RSI, which helps to lock in profits.
Backtesting results should be analysed to optimize the DI Length and RSI parameters for specific instruments.
Optimized Impulse Wave Strategy for Speedy BTC Trades (3-Min)Looking to capitalize on rapid price movements in Bitcoin? The Optimized Impulse Wave Strategy is designed for high-frequency traders who thrive on short-term opportunities. Leveraging a combination of key technical indicators, this strategy aims to provide timely entries and exits with dynamic risk management.
Key Features:
📊 Indicators Used:
MACD Crossover: To identify momentum shifts.
200 EMA Trend Confirmation: For directional bias.
RSI (14): To gauge overbought/oversold conditions.
ADX (14): To confirm strong trends with a threshold filter.
ATR-based Stop Loss & Take Profit: Adaptive risk management.
⚡ Timeframe: 3-minute chart – ideal for scalping and short-term trades.
💡 Entry Logic:
Long Entry: Price above EMA, MACD bullish crossover, RSI > 50, and ADX strength confirmation.
Short Entry: Price below EMA, MACD bearish crossover, RSI < 50, and ADX strength confirmation.
🎯 Risk-Reward Ratio: Customizable with built-in ATR calculations to ensure strategic exits.
Performance:
✅ Win Rate: ~40% on BTC/USDT (3-min timeframe) in backtesting.
✅ Profit Factor: Carefully optimized to balance risk and reward.
✅ Trade Frequency: Frequent, perfect for active traders seeking volatility.
How to Use:
Apply the script to BTC/USDT on the 3-minute chart.
Watch for green buy arrows and red sell arrows to trigger trades.
Manage your risk using ATR-based stop-loss and take-profit levels.
Enable alerts for real-time trade signals.
⚠ Disclaimer: Past performance does not guarantee future results. Use proper risk management and test in a demo environment before live trading.
Follow for more trading strategies and share your thoughts below! 📩🔥
Breaker & Double Top/Low Detector (Last 100 Candles)//@version=5
indicator("Breaker & Double Top/Low Detector (Last 100 Candles)", overlay=true)
// Input parameters
length = 100 // Fixed lookback length of 100 candles
threshold = input.float(0.5, title="Threshold (%)", minval=0.1, step=0.1)
// Helper functions
isBreaker(highs, lows) =>
// Identify a Breaker pattern when a resistance/support level is broken in the last 100 candles
prevHigh = ta.highest(highs, length)
prevLow = ta.lowest(lows, length)
close > prevHigh or close < prevLow
isDoubleTop(highs) =>
// Identify Double Top when two recent peaks are nearly equal within threshold in the last 100 candles
topPivot = ta.pivothigh(highs, length, length) // Find local peak
nextTopPivot = ta.pivothigh(highs , length, length) // Second local peak
isDoubleTop = not na(topPivot) and not na(nextTopPivot) and
math.abs(high - high ) / high <= threshold / 100 and
ta.barssince(topPivot) <= length // Ensure the pivot is within the last 100 candles
isDoubleTop
isDoubleLow(lows) =>
// Identify Double Low when two recent valleys are nearly equal within threshold in the last 100 candles
lowPivot = ta.pivotlow(lows, length, length) // Find local valley
nextLowPivot = ta.pivotlow(lows , length, length) // Second local valley
isDoubleLow = not na(lowPivot) and not na(nextLowPivot) and
math.abs(low - low ) / low <= threshold / 100 and
ta.barssince(lowPivot) <= length // Ensure the pivot is within the last 100 candles
isDoubleLow
// Pattern identification
breakerSignal = isBreaker(high, low) // Breaker pattern
doubleTopSignal = isDoubleTop(high) // Double Top
doubleLowSignal = isDoubleLow(low) // Double Low
// Plot signals
plotshape(breakerSignal, title="Breaker", location=location.abovebar, color=color.red, style=shape.labelup, text="Breaker")
plotshape(doubleTopSignal, title="Double Top", location=location.abovebar, color=color.orange, style=shape.labelup, text="DTop")
plotshape(doubleLowSignal, title="Double Low", location=location.belowbar, color=color.green, style=shape.labeldown, text="DLow")
// Background coloring
bgcolor(breakerSignal ? color.new(color.red, 90) : na, title="Breaker Background")
bgcolor(doubleTopSignal ? color.new(color.orange, 90) : na, title="Double Top Background")
bgcolor(doubleLowSignal ? color.new(color.green, 90) : na, title="Double Low Background")
// Debugging for values
if (breakerSignal)
label.new(bar_index, high, "Breaker")
if (doubleTopSignal)
label.new(bar_index, high, "Double Top")
if (doubleLowSignal)
label.new(bar_index, low, "Double Low")
Export Datathis script widmsfsnklfdsmsfklmdklmskldskl;mgfksldmgklsdmglksdfnmgkldsmngvlksdmnvlkdmsnklvndsklvnsdklv ndvdsklvdsklvlksdvmsdklmvsldkkvd
Turn of the Month Strategy on Steroids█ STRATEGY DESCRIPTION
The "Turn of the Month Strategy on Steroids" is a seasonal mean-reversion strategy designed to capitalize on price movements around the end of the month. It enters a long position when specific conditions are met and exits when the Relative Strength Index (RSI) indicates overbought conditions. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE TURN OF THE MONTH EFFECT?
The Turn of the Month effect refers to the observed tendency of stock prices to rise around the end of the month. This strategy leverages this phenomenon by entering long positions when the price shows signs of a reversal during this period.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day of the month is greater than or equal to the specified `dayOfMonth` threshold (default is 25).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
There is no existing open position (`strategy.position_size == 0`).
2. EXIT CONDITION
A Sell Signal is generated when the 2-period RSI exceeds 65, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Day of Month: The day of the month threshold for triggering a Buy Signal. Default is 25.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed to exploit seasonal price patterns around the end of the month.
It performs best in markets where the Turn of the Month effect is pronounced.
Backtesting results should be analyzed to optimize the `dayOfMonth` threshold and RSI parameters for specific instruments.
5-8-13 MA Crossover Signals with Arrows (Short Term)//@version=5
indicator("5-8-13 MA Crossover Signals with Arrows", overlay=true)
// Hareketli ortalamaları tanımla
ma5 = ta.sma(close, 5)
ma8 = ta.sma(close, 8)
ma13 = ta.sma(close, 13)
// Kesişim noktalarını belirle
bullishCross = ta.crossover(ma5, ma13)
bearishCross = ta.crossunder(ma5, ma13)
// Yeşil ve kırmızı ok işaretlerini çiz
plotshape(series=bullishCross, location=location.belowbar, color=color.new(color.green, 0), style=shape.labelup, size=size.small, title="Bullish Crossover")
plotshape(series=bearishCross, location=location.abovebar, color=color.new(color.red, 0), style=shape.labeldown, size=size.small, title="Bearish Crossover")
// Hareketli ortalamaları çizin
plot(ma5, color=color.blue, title="5 MA")
plot(ma8, color=color.orange, title="8 MA")
plot(ma13, color=color.purple, title="13 MA")
Candlestick Pattern Volume AnalysisBearish Engulfing Pattern - This script now fully handles Bullish Engulfing, Bearish Engulfing, Bullish Hammer, and Bearish Hammer patterns with volume-based breakout signals. Let me know if you need further modifications
NY Liquidity sweep - MuralidharNew York Session Liquidity Sweep in the Asian Session
This term refers to a price action phenomenon where liquidity created during the New York trading session is targeted and swept (or cleared) during the subsequent Asian trading session. Let’s break this down:
Key Components:
Liquidity:
In financial markets, liquidity often refers to the areas where stop-loss orders, pending orders, or clusters of trades accumulate. These areas typically form around key levels like highs, lows, or consolidation zones.
Traders often place stop-losses above recent highs or below recent lows, creating "pools of liquidity."
New York Session:
The New York session is one of the most volatile trading sessions due to the overlap with the London session and the significant participation of institutional players.
It often leaves behind key levels, such as session highs, lows, or consolidation zones, where liquidity builds up.
Asian Session:
The Asian session is typically less volatile compared to the New York session. However, it can still be used by market makers or large players to manipulate price action.
Due to the reduced trading volume, it is easier for large players to sweep liquidity during this session.
What Happens During a Liquidity Sweep?
Formation of Liquidity Zones in the New York Session:
As the New York session progresses, traders establish positions, leaving behind liquidity pockets such as stop-loss orders around session highs and lows.
Asian Session Sweep:
In the quieter Asian session, price often moves to these liquidity zones created during the New York session.
This "sweep" is often a sharp move in price designed to trigger stop-loss orders or entice breakout traders into the market.
Once the liquidity is taken, price often reverses sharply, leaving behind a false breakout or a wick in the price chart.
Why Does This Happen?
Market Maker Behavior:
Market makers or large institutional players may manipulate prices to access liquidity.
By sweeping these zones, they can fill their larger orders at better prices.
Inducing Traders:
A sweep may be used to lure retail traders into positions before reversing the market direction, trapping them.
Practical Implications for Traders:
Identifying Liquidity Zones:
Mark key highs, lows, and consolidation areas from the New York session on your charts.
Watch for price action around these zones during the Asian session.
Avoiding Traps:
Be cautious of trading breakouts during the Asian session, as they might be liquidity grabs.
Look for confirmation before entering trades.
Using the Sweep to Your Advantage:
After the sweep, wait for signs of reversal, such as candlestick patterns or rejection wicks, to enter trades in the opposite direction.
Example:
During the New York session, a high is formed at 1.2000 on EUR/USD.
In the Asian session, price moves up to 1.2005, triggering stop-loss orders placed above 1.2000.
After the sweep, price sharply reverses, leaving a wick at 1.2005 and continuing downward.
By understanding this phenomenon, traders can better anticipate market behavior and refine their strategies to avoid being caught in liquidity traps.
Multi-Condition Alert ScriptA Grok written Script/Alert I use for triggering a Sell on my DCA Bots. Sends an alert using an OR operator on 3 separate conditions. Any of the three conditions can trigger an alert based on user settings.
Written in Pine 5, but should convert to 6 ok.
The three conditions are:
1. Moving Average Convergence - can select SMA or EMA and the fast and slow values. Script will send an alert based on the distance between the 2 values converging by a user selected percentage (E.G. alert when fast MA and slow MA gap closes by x%)
2. Counts Candles - Select Red or Green. I use it to count 3 consecutive red candles with a minimum 0.1 percent size. User can select number of candles and minimum percentage size to be counted. Red or green use positive values for the percentage in the dialogue. The script normalizes it.
3. RSI - user can choose period, value and crossing up or down as well as greater than or less than values.
If any of the three conditions, based on the user's selections becomes true - then an alert is sent.
The script begins a cycle when the fast MA crosses up the slow MA value. Timeframes are user defined for the alerts. I usually use 3M, 5M and 15M depending on the bot, but any value should work.
For candles, it resets its counter each time a condition is met (E.G. 3 consecutive red will start counting again at 0 with next candle)
In theory it would work counting green candles going up, but I have only used it to trigger sell events. And remember it starts its cycle when fast MA crosses up slow MA.
Use at your own risk. I provide no warranties or guarantees.
Feel free to use or modify for your own personal use. Not for sale or resale.
Definitive Trend Prediction%100 kesin sonuç beklemek yanıltıcıdır; piyasa haberleri, ani volatilite değişiklikleri veya ekonomik olaylar gibi dış faktörler stratejiyi etkileyebilir.
ETH/USD MACD CrossoverMACD visual buy and sell when MACD is crossed over, overlay on chart, signal alerts. free to use, Thank you.
Yesterday's Close and Today's OpenAn Intraday trading strategy when candle 5 or 15 min complete closed then take a trade
xrp 1. Technical Indicators
XRP’s price action can be analyzed using standard technical analysis tools, which help traders identify trends, momentum, and potential reversal points. Key technical indicators include:
• Moving Averages (MA):
• Simple Moving Average (SMA) or Exponential Moving Average (EMA) to track trends over time.
• Look for crossovers (e.g., 50-day EMA crossing above 200-day EMA is bullish).
• Relative Strength Index (RSI):
• Measures overbought or oversold conditions.
• RSI above 70 indicates overbought (potential reversal down); below 30 indicates oversold (potential reversal up).
• MACD (Moving Average Convergence Divergence):
• Identifies trend strength and momentum.
• A bullish crossover (MACD line crossing above the signal line) may indicate upward momentum.
• Support and Resistance Levels:
• Historical price levels where XRP often reverses or consolidates.
• These levels are crucial for identifying potential entry and exit points.
• Volume:
• Look for increases in volume to confirm the strength of price movements.
• High volume during a breakout can signal a strong continuation of the trend.
• Bollinger Bands:
• Useful for gauging volatility.
• When the bands widen, volatility is high; when they narrow, the price may consolidate or prepare for a breakout.
Sessions [MiAn]A session script is a set of commands or instructions that are executed in a specific order to automate tasks, interact with systems, or perform other actions.
Here's a general breakdown of what a session script typically includes:
1. *Initialization*: The script initializes the session, which may involve setting up environment variables, loading libraries or modules, or establishing connections to external systems.
2. *Commands or Instructions*: The script executes a series of commands or instructions, which can include tasks such as:
- Data processing or manipulation
- File operations (e.g., copying, moving, deleting)
- System interactions (e.g., launching applications, sending notifications)
- Network interactions (e.g., sending requests, receiving data)
3. *Logic and Control Flow*: The script may include conditional statements, loops, and other control structures to manage the flow of execution based on various conditions or inputs.
4. *Error Handling*: The script may include error handling mechanisms to catch and manage errors or exceptions that occur during execution.
5. *Cleanup*: The script may perform cleanup tasks, such as closing connections, releasing resources, or deleting temporary files.
Session scripts can be written in various programming languages, such as shell scripts (e.g., Bash, PowerShell), Python, or other scripting languages.
What specific type of session script are you interested in learning more about?
Last Week Close and Current Week Opentrade buy upside breakout of green line and viceversa for sell on opposite side
CPR WITH PIVOT LEVEL + 3 EMA BY HSEGet CPR, PIVOT LEVELS, PDH, PDL, and 3 EMA'S in single indicator.
ATH ve Trend Dip İndikatörüATH en yüksel tepe(kırmızı) düşen tepe (mavi) ve dip bölge Trend İndikatörü
6 EMA's with BUY/SELL by Lincoln Khan -V2This Pine Script, titled "6 EMA's with BUY/SELL by Lincoln Khan," is designed to assist traders in identifying trends and potential trading opportunities based on exponential moving averages (EMAs). It visualizes six EMAs with user-defined colors and periods, allowing traders to observe market momentum and potential reversal points. The script provides clear Buy and Sell signals based on the crossover of specific EMAs, helping traders make informed decisions.
