Heikin Ashi - RSI - SMA +/- Color Timeframe / Symbol- ENThis code includes a simple method to recolor standard Heikin Ashi candlesticks based on RSI or SMA conditions. Different crypto symbols or different timeframes can be selected.
- RSI1 > RSI2 : green: red
- SMA1 > SMA2 : green : red
Indicators and strategies
Motion Sentinel - Testing 01Script de prueba Motion Sentinel.
Motion analiza patrones dentro de acciones y busca validaciones operativas en ellos para construir y mantener una ventaja estadística.
Bitcoin MVRV Z-Score OverlayThis indicator overlays a buy and sell threshold onto a BTCUSD chart. These thresholds are calculated using the MVRV Z-Score and the provided threshold values for the MVRV Z-Score.
Enhanced Market Analyzer with Adaptive Cognitive LearningThe "Enhanced Market Analyzer with Advanced Features and Adaptive Cognitive Learning" is an advanced, multi-dimensional trading indicator that leverages sophisticated algorithms to analyze market trends and generate predictive trading signals. This indicator is designed to merge traditional technical analysis with modern machine learning techniques, incorporating features such as adaptive learning, Monte Carlo simulations, and probabilistic modeling. It is ideal for traders who seek deeper market insights, adaptive strategies, and reliable buy/sell signals.
Key Features:
Adaptive Cognitive Learning:
Utilizes Monte Carlo simulations, reinforcement learning, and memory feedback to adapt to changing market conditions.
Adjusts the weighting and learning rate of signals dynamically to optimize predictions based on historical and real-time data.
Hybrid Technical Indicators:
Custom RSI Calculation: An RSI that adapts its length based on recursive learning and error adjustments, making it responsive to varying market conditions.
VIDYA with CMO Smoothing: An advanced moving average that incorporates Chander Momentum Oscillator for adaptive smoothing.
Hamming Windowed VWMA: A volume-weighted moving average that applies a Hamming window for smoother calculations.
FRAMA: A fractal adaptive moving average that responds dynamically to price movements.
Advanced Statistical Analysis:
Skewness and Kurtosis: Provides insights into the distribution and potential risk of market trends.
Z-Score Calculations: Identifies extreme market conditions and adjusts trading thresholds dynamically.
Probabilistic Monte Carlo Simulation:
Runs thousands of simulations to assess potential price movements based on momentum, volatility, and volume factors.
Integrates the results into a probabilistic signal that informs trading decisions.
Feature Extraction:
Calculates a variety of market metrics, including price change, momentum, volatility, volume change, and ATR.
Normalizes and adapts these features for use in machine learning algorithms, enhancing signal accuracy.
Ensemble Learning:
Combines signals from different technical indicators, such as RSI, MACD, Bollinger Bands, Stochastic Oscillator, and statistical features.
Weights each signal based on cumulative performance and learning feedback to create a robust ensemble signal.
Recursive Memory and Feedback:
Stores and averages past RSI calculations in a memory array to provide historical context and improve future predictions.
Adaptive memory factor adjusts the influence of past data based on current market conditions.
Multi-Factor Dynamic Length Calculation:
Determines the length of moving averages based on volume, volatility, momentum, and rate of change (ROC).
Adapts to various market conditions, ensuring that the indicator is responsive to both high and low volatility environments.
Adaptive Learning Rate:
The learning rate can be adjusted based on market volatility, allowing the system to adapt its speed of learning and sensitivity to changes.
Enhances the system's ability to react to different market regimes.
Monte Carlo Simulation Engine:
Simulates thousands of random outcomes to model potential future price movements.
Weights and aggregates these simulations to produce a final probabilistic signal, providing a comprehensive risk assessment.
RSI with Dynamic Adjustments:
The initial RSI length is adjusted recursively based on calculated errors between true RSI and predicted RSI.
The adaptive RSI calculation ensures that the indicator remains effective across various market phases.
Hybrid Moving Averages:
Short-Term and Long-Term Averages: Combines FRAMA, VIDYA, and Hamming VWMA with specific weights for a unique hybrid moving average.
Weighted Gradient: Applies a color gradient to indicate trend strength and direction, improving visual clarity.
Signal Generation:
Generates buy and sell signals based on the ensemble model and multi-factor analysis.
Uses percentile-based thresholds to determine overbought and oversold conditions, factoring in historical data for context.
Optional settings to enable adaptation to volume and volatility, ensuring the indicator remains effective under different market conditions.
Monte Carlo and Learning Parameters:
Users can customize the number of Monte Carlo simulations, learning rate, memory factor, and reward decay for tailored performance.
Applications:
Scalping and Day Trading:
The fast response of the adaptive RSI and ensemble learning model makes this indicator suitable for short-term trading strategies.
Swing Trading:
The combination of long-term moving averages and probabilistic models provides reliable signals for medium-term trends.
Volatility Analysis:
The ATR, Bollinger Bands, and adaptive moving averages offer insights into market volatility, helping traders adjust their strategies accordingly.
OOPS ReversalOOPS Reversal made famous by billionaire trades manrav and TSDR TRADING in the hedge fund Uncharted Territory
10 EMA Break with Volume ConfirmationTracks when price breaks above or below 10 EMA with above average volume useful for meaningful breaks above or below as well as false breaks with easy to read icons
enjoy :)
Volatility Screenercomaparing volatility of last 5 days with respect to last 20 days just to indeintyf
10 DMA and 20 DMA Crossover with Candle Confirmation10 DMA and 20 DMA Crossover with Candle Confirmation
ameer hamza indicator//@version=5
strategy("Simplified EMA + RSI Strategy", overlay=true)
// Input settings
emaShort = input.int(10, title="Short EMA Length", minval=1)
emaLong = input.int(30, title="Long EMA Length", minval=1)
rsiLength = input.int(14, title="RSI Length")
rsiOverbought = input.int(70, title="RSI Overbought Level", minval=50, maxval=100)
rsiOversold = input.int(30, title="RSI Oversold Level", minval=0, maxval=50)
stopLossPct = input.float(1.0, title="Stop Loss Percentage") / 100
takeProfitPct = input.float(2.0, title="Take Profit Percentage") / 100
// Indicators
emaShortLine = ta.ema(close, emaShort)
emaLongLine = ta.ema(close, emaLong)
rsi = ta.rsi(close, rsiLength)
// Plot EMA lines
plot(emaShortLine, color=color.blue, title="Short EMA")
plot(emaLongLine, color=color.red, title="Long EMA")
hline(rsiOverbought, "RSI Overbought", color=color.orange)
hline(rsiOversold, "RSI Oversold", color=color.green)
// Buy and Sell Conditions
longCondition = crossover(emaShortLine, emaLongLine) and rsi < rsiOverbought
shortCondition = crossunder(emaShortLine, emaLongLine) and rsi > rsiOversold
// Debugging
if (longCondition)
label.new(bar_index, high, "Long Entry", color=color.green, textcolor=color.white)
if (shortCondition)
label.new(bar_index, low, "Short Entry", color=color.red, textcolor=color.white)
// Entry Signals
if (longCondition)
strategy.entry("Long", strategy.long)
if (shortCondition)
strategy.entry("Short", strategy.short)
// Stop Loss and Take Profit
longStopLoss = strategy.position_avg_price * (1 - stopLossPct)
longTakeProfit = strategy.position_avg_price * (1 + takeProfitPct)
shortStopLoss = strategy.position_avg_price * (1 + stopLossPct)
shortTakeProfit = strategy.position_avg_price * (1 - takeProfitPct)
if (strategy.position_size > 0)
strategy.exit("Exit Long", stop=longStopLoss, limit=longTakeProfit)
if (strategy.position_size < 0)
strategy.exit("Exit Short", stop=shortStopLoss, limit=shortTakeProfit)
ViganThe Vigan is a range bound momentum oscillator. This is designed to display the advance location of the close compared to the high/low range over a user defined number of periods. Typically, this is used for three things; Identifying overbought and oversold levels, spotting divergences and also identifying bull and bear set ups or signals.
QUOTEX lIVE Market Signal By XadikuLTo enhance the strategy further, I'll add additional candlestick pattern confirmations commonly used for identifying potential reversals. In addition to bullish engulfing and bearish engulfing, I’ll include:
Hammer: A single candlestick pattern that suggests a potential reversal at the bottom of a downtrend.
Inverted Hammer: A single candlestick pattern that suggests a potential reversal at the bottom of a downtrend.
Shooting Star: A single candlestick pattern indicating a potential reversal at the top of an uptrend.
Doji: A pattern that represents market indecision and could suggest a reversal when combined with other conditions.
Here’s the updated script with additional candlestick pattern confirmations:
SLYY BTC Strategy – Dynamische Trend- und Volatilitätsbasierte Die SLYY BTC Strategy ist eine speziell entwickelte Strategie für den BTC-Handel, die durch eine Kombination von gleitenden Durchschnitten und einem ATR-basierten Filter besonders stabile Ein- und Ausstiege ermöglicht. Der Algorithmus nutzt den 111er und 350er gleitenden Durchschnitt, um grundlegende Marktrichtungen zu erkennen und Entry-Trigger zu setzen. Zusätzlich stellt der ATR-Indikator (Average True Range) sicher, dass Trades nur bei optimaler Marktvolatilität ausgeführt werden, wodurch unnötige Risiken minimiert werden.
Funktionen der Strategie:
• Dynamischer Stop-Loss: Der Stop-Loss passt sich automatisch an die aktuelle Volatilität an und wird auf Basis eines variablen ATR-Multiplikators gesetzt, sodass er in volatilen Phasen breiter und in stabilen Phasen enger ist.
• Flexibler Trade-Einstieg: Die Strategie erkennt Long- und Short-Signale basierend auf den gleitenden Durchschnitten und eröffnet Positionen nur, wenn der ATR unter einem definierten Schwellenwert liegt.
• Zuverlässiges Risikomanagement: Die Stop-Loss-Abstände basieren auf einem fixen prozentualen Offset, der in den Strategieeinstellungen angepasst werden kann, um den persönlichen Risikopräferenzen zu entsprechen.
Einsatzgebiet:
Diese Strategie ist für Trader geeignet, die BTC auf mittleren Zeitrahmen handeln und ein risikokontrolliertes System mit dynamischem Volatilitätsmanagement bevorzugen. Die Slice PTC Strategy bietet eine klare, algorithmische Lösung für den Handel in Trendphasen und stabilisiert die Performance durch eine intelligente Volatilitätssteuerung.
Smoothed Moving Average ModifiedStandard SMMA. An input called offset is only added which allows the user to specify an integer value to move the SMMA. A positive value will move the average forward (to the right), while a negative value will move it backward (to the left) relative to current prices.
Highlight 9:15 AM to 3:30 PM ISTindian share market time. this time frame you can used with cryptotrading session, dow jones
5% Close Move CandlesCANDLE ABOVE 5% MOVE
Close-to-Close Calculation: The script calculates the percentage change in closing prices compared to the previous day.
Highlighting: Candles with a 5% or greater close-to-close move are highlighted with a blue background.
Label: A label above each qualifying candle displays the percentage change.
EMA Cross Indicator with SignalEMA Cross Indicator with LONG & SHORT Signals
This code adds two new plotshape() functions to display text labels ("Buy Signal" and "Sell Signal") at the points of the crossovers. You can further customize the appearance of these labels by adjusting the text, style, location, color, text colour, and size parameters.
Remember to thoroughly test this indicator on historical data to evaluate its effectiveness and adjust parameters.
Cuanterousss Trend//@version=5
indicator("Follow Trend EMA Volume", overlay=true)
/// Mengatur panjang EMA yang dibutuhkan
ema5 = ta.ema(close, 5)
ema7 = ta.ema(close, 7)
ema21 = ta.ema(close, 21)
ema34 = ta.ema(close, 34)
ema55 = ta.ema(close, 55)
ema90 = ta.ema(close, 90)
ema100 = ta.ema(close, 100)
ema161 = ta.ema(close, 161)
ema200 = ta.ema(close, 200)
/// Menghitung rata-rata EMA untuk menentukan tren dominan
ema_avg = (ema5 + ema7 + ema21 + ema34 + ema55 + ema90 + ema100 + ema161 + ema200) / 9
/// Menghitung volume rata-rata untuk menyaring sinyal
vol_avg = ta.sma(volume, 20) // Volume rata-rata 20 periode
/// Aturan untuk trend dominan berdasarkan posisi harga terhadap EMA rata-rata
bullish_trend = close > ema_avg and volume > vol_avg
bearish_trend = close < ema_avg and volume > vol_avg
Period MarkerThis Period Marker Indicator for TradingView is a visual tool that allows you to highlight a specific date range on your chart. It uses a shaded background color to mark the defined period, making it easy to visually separate and focus on specific time intervals. This is especially useful for analyzing historical events, comparing specific timeframes, or marking earnings seasons or other critical periods in price action.
Key Features
Easy Date Range Selection:
The indicator has a calendar-style date input for both the start and end dates. This allows for quick and precise selection of date ranges without manually entering each date component (year, month, day).
Customizable Period Highlight:
When active, the indicator shades the background of the chart over the specified period. The default highlight color is a semi-transparent green, but this can be customized within the script to any color and opacity you prefer.
The shaded background helps you easily identify and focus on the defined date range.
Dynamic Adjustment:
You can adjust the start and end dates in real-time, and the background shading will automatically update to reflect the new period, allowing flexibility in testing and viewing multiple periods quickly.
Practical Uses
Event Marking: Track significant historical events (e.g., economic data releases, geopolitical events) to see their effects on price action.
Seasonal Analysis: Highlight and compare seasonal trends, such as quarterly earnings or year-end rallies, across multiple years.
Backtesting Specific Periods: When analyzing strategies, you can visually isolate specific date ranges to review performance or behavior in defined intervals.
The Period Marker Indicator is a simple yet effective way to enhance time-based analysis on TradingView, helping you gain insights by focusing on relevant periods with ease.
