Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Cerca negli script per "Exponential Moving Average"
EMA and VWAP by Phil VoEMA and VWAP by Phil Vo
Description
This indicator combines two powerful technical analysis tools: Exponential Moving Averages (EMAs) and Volume Weighted Average Price (VWAP). Designed to assist traders in identifying trends and key price levels, this script overlays two customizable EMAs and a daily VWAP on your chart.
* EMA 1 (Blue): A fast-moving EMA with a default period of 9, ideal for short-term trend analysis.
* EMA 2 (Red): A slower EMA with a default period of 21, useful for confirming longer-term trends.
* VWAP (Yellow): The Volume Weighted Average Price, calculated using the typical price (HLC3) and volume, resetting daily. It serves as a dynamic support/resistance level and reflects the average price weighted by volume.
Features
* Customizable EMAs: Adjust the periods of both EMAs via the settings (minimum period: 1).
* Visual Clarity: Each line is plotted in a distinct color (Blue for EMA 1, Red for EMA 2, Yellow for VWAP) with a linewidth of 2 for easy identification.
* Daily VWAP: The VWAP resets at the start of each trading day, providing a reliable intraday reference point.
* Tooltips: Hover over the input settings to see descriptions of each EMA period.
How to Use
1. Add the indicator to your chart.
2. Customize the EMA periods in the settings if desired (defaults are 9 and 21).
3. Use the EMAs to spot trends:
* When EMA 1 crosses above EMA 2, it may signal a bullish trend.
* When EMA 1 crosses below EMA 2, it may indicate a bearish trend.
4. Use the VWAP as a dynamic support/resistance level:
* Prices above VWAP might suggest bullish momentum.
* Prices below VWAP might indicate bearish pressure.
Settings
* EMA 1 Length: Set the period for the fast EMA (default: 9).
* EMA 2 Length: Set the period for the slow EMA (default: 21).
Notes
* The VWAP resets daily by default, making it most suitable for intraday trading.
* This script is open-source under the Mozilla Public License 2.0, so feel free to study or modify it!
Author
Created by Phil Vo. Happy trading!
How to Add This to TradingView
When you publish the script:
1. Paste the description above into the "Description" field in the "Publish Script" dialog.
2. Set the title as "EMA and VWAP by Phil Vo".
3. Choose "Public" visibility and "Open" access to share it with the community.
4. Add tags like "EMA", "VWAP", "Moving Average", "Trend", and "Volume" to help users find it.
This description provides a clear explanation of the indicator’s purpose, usage instructions, and customization options, making it accessible and helpful for TradingView users. Let me know if you’d like to adjust anything!
EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)
🚨 Main Utility: Early Squeeze Warning
The primary function of this indicator is to warn traders early when the market is approaching a "squeeze"—a tightening condition that often precedes significant moves or regime shifts. By visually highlighting areas of increasing tension, it helps traders anticipate potential volatility and prepare accordingly. This is intended to be a statistically and psychologically grounded replacement of so-called "fib-time-zones," which are overly-deterministic and subjective.
📌 Overview
The EMA-Based Squeeze Dynamics indicator projects future regime shifts (such as golden and death crosses) using exponential moving averages (EMAs). It employs historical interval data and current market conditions to dynamically forecast when the critical EMAs (50-period and 200-period) will reconverge, marking likely trend-change points.
This indicator leverages two core ideas:
Behavioral finance theory: Traders often collectively anticipate popular EMA crossovers, creating a self-fulfilling prophecy (normative social influence), similar to findings from Solomon Asch’s conformity experiments.
Bayesian-like updates: It utilizes historical crossover intervals as a prior, dynamically updating expectations based on evolving market data, ensuring its signals remain objectively grounded in actual market behavior.
⚙️ Technical & Mathematical Explanation
1. EMA Calculations and Regime Definitions
The indicator uses three EMAs:
Fast (9-period): Represents short-term price movement.
Medial (50-period): Indicates medium-term trend direction.
Slow (200-period): Defines long-term market sentiment.
Regime States:
Bullish: 50 EMA is above the 200 EMA.
Bearish: 50 EMA is below the 200 EMA.
A shift between these states triggers visual markers (arrows and labels) directly on the chart.
2. Gap Dynamics and Historical Intervals
At each crossover:
The indicator records the gap (distance) between the 50 and 200 EMAs.
It tracks the historical intervals between past crossovers.
An Exponentially Weighted Moving Average (EWMA) of these intervals is calculated, weighting recent intervals more heavily, dynamically updating expectations.
Important note:
After every regime shift, the projected crossover line resets its calculation. This reset is visually evident as the projection line appears to move further away after each regime change, temporarily "repelled" until the EMAs begin converging again. This ensures projections remain realistic, grounded in actual EMA convergence, and prevents overly optimistic forecasts immediately after a regime shift.
3. Gap Momentum & Adaptive Scaling
The indicator measures how quickly or slowly the gap between EMAs is changing ("gap momentum") and adjusts its forecast accordingly:
If the gap narrows rapidly, a crossover becomes more imminent.
If the gap widens, the next crossover is pushed further into the future.
The "gap factor" dynamically scales the projection based on recent gap momentum, bounded between reasonable limits (0.7–1.3).
4. Squeeze Ratio & Background Color (Visual Cues)
A "squeeze ratio" is computed when market conditions indicate tightening:
In a bullish regime, if the fast EMA is below the medial EMA (price pulling back towards long-term support), the squeeze ratio increases.
In a bearish regime, if the fast EMA rises above the medial EMA (price rallying into long-term resistance), the squeeze ratio increases.
What the Background Colors Mean:
Red Background: Indicates a bullish squeeze—price is compressing downward, hinting a bullish reversal or continuation breakout may occur soon.
Green Background: Indicates a bearish squeeze—price is compressing upward, suggesting a bearish reversal or continuation breakout could soon follow.
Opacity Explanation:
The transparency (opacity) of the background indicates the intensity of the squeeze:
High Opacity (solid color): Strong squeeze, high likelihood of imminent volatility or regime shift.
Low Opacity (faint color): Mild squeeze, signaling early stages of tightening.
Thus, more vivid colors serve as urgent visual warnings that a squeeze is rapidly intensifying.
5. Projected Next Crossover and Pseudo Crossover Mechanism
The indicator calculates an estimated future bar when a crossover (and thus, regime shift) is expected to occur. This calculation incorporates:
Historical EWMA interval.
Current squeeze intensity.
Gap momentum.
A dynamic penalty based on divergence from baseline conditions.
The "Pseudo Crossover" Explained:
A key adaptive feature is the pseudo crossover mechanism. If price action significantly deviates from the projected crossover (for example, if price stays beyond the projected line longer than expected), the indicator acknowledges the projection was incorrect and triggers a "pseudo crossover" event. Essentially, this acts as a reset, updating historical intervals with a weighted adjustment to recalibrate future predictions. In other words, if the indicator’s initial forecast proves inaccurate, it recognizes this quickly, resets itself, and tries again—ensuring it remains responsive and adaptive to actual market conditions.
🧠 Behavioral Theory: Normative Social Influence
This indicator is rooted in behavioral finance theory, specifically leveraging normative social influence (conformity). Traders commonly watch EMA signals (especially the 50 and 200 EMA crossovers). When traders collectively anticipate these signals, they begin trading ahead of actual crossovers, effectively creating self-fulfilling prophecies—similar to Solomon Asch’s famous conformity experiments, where individuals adopted group behaviors even against direct evidence.
This behavior means genuine regime shifts (actual EMA crossovers) rarely occur until EMAs visibly reconverge due to widespread anticipatory trading activity. The indicator quantifies these dynamics by objectively measuring EMA convergence and updating projections accordingly.
📊 How to Use This Indicator
Monitor the background color and opacity as primary visual cues.
A strongly colored background (solid red/green) is an early alert that a squeeze is intensifying—prepare for potential volatility or a regime shift.
Projected crossover lines give a dynamic target bar to watch for trend reversals or confirmations.
After each regime shift, expect a reset of the projection line. The line may seem initially repelled from price action, but it will recalibrate as EMAs converge again.
Trust the pseudo crossover mechanism to automatically recalibrate the indicator if its original projection misses.
🎯 Why Choose This Indicator?
Early Warning: Visual squeeze intensity helps anticipate market breakouts.
Behaviorally Grounded: Leverages real trader psychology (conformity and anticipation).
Objective & Adaptive: Uses real-time, data-driven updates rather than static levels or subjective analysis.
Easy to Interpret: Clear visual signals (arrows, labels, colors) simplify trading decisions.
Self-correcting (Pseudo Crossovers): Quickly adjusts when initial predictions miss, maintaining accuracy over time.
Summary:
The EMA-Based Squeeze Dynamics Indicator combines behavioral insights, dynamic Bayesian-like updates, intuitive visual cues, and a self-correcting pseudo crossover feature to offer traders a reliable early warning system for market squeezes and impending regime shifts. It transparently recalibrates after each regime shift and automatically resets whenever projections prove inaccurate—ensuring you always have an adaptive, realistic forecast.
Whether you're a discretionary trader or algorithmic strategist, this indicator provides a powerful tool to navigate market volatility effectively.
Happy Trading! 📈✨
Futuristic Indicator v3 - Enhanced Glow & Strength MetersTo ensure candles are display by script go to trading view settings and uncheck default Candle, Body and Wick to prevent them from plotting over your modified candles.
Futuristic Indicator v3 - Enhanced Glow & Strength Meters: Detailed Breakdown
This Modern styled Pine Script indicator is designed to enhance technical analysis by providing a visually striking OLED-style dashboard with multiple market insights. It integrates trend detection, momentum analysis, volatility tracking, and strength meters into a single, streamlined interface for traders.
1️⃣ Customizable Features for Flexibility
The indicator offers multiple user-configurable settings, allowing traders to adjust the display based on their trading strategy and preferences. Users can toggle elements such as strength meters, volatility indicators, trend arrows, moving averages, and buy/sell alerts. Additionally, background and candle colors can be customized for better readability.
🔹 Why is this useful?
Traders can customize their charts to focus on the data they care about.
Reduces chart clutter by allowing users to toggle features on or off.
2️⃣ Trend Detection Using EMAs
This indicator detects market trends using two Exponential Moving Averages (EMA):
A "Fast" EMA (shorter period) for quick trend shifts.
A "Slow" EMA (longer period) to confirm trends.
Comparison of the two EMAs determines if the trend is bullish (uptrend) or bearish (downtrend).
The indicator colors the trend lines accordingly and adds a trend arrow 📈📉 for quick visual cues.
🔹 Why is this useful?
EMA crossovers are widely used to identify trend reversals.
Provides clear visual cues for traders to confirm entry & exit points.
3️⃣ RSI-Based Momentum Analysis
The indicator integrates the Relative Strength Index (RSI) to gauge market momentum. The momentum value changes color dynamically based on whether it's in bullish (>50) or bearish (<50) territory.
🔹 Why is this useful?
RSI helps identify overbought and oversold conditions.
Detects trend strength by measuring the speed of price movements.
4️⃣ Bullish & Bearish Strength Meters
The indicator quantifies bullish and bearish market strength based on RSI and converts it into a percentage-based meter:
Bullish Strength (Long Strength)
Bearish Strength (Short Strength)
Strength meters are displayed using OLED-styled bars, dynamically changing in real-time.
🔹 Why is this useful?
Allows traders to visually gauge market sentiment at a glance.
Helps confirm if a trend has strong momentum or is losing strength.
5️⃣ Market Volatility Indicator (ATR-Based)
The indicator includes a volatility tracker using the Average True Range (ATR):
ATR is scaled up to provide easier readability.
Higher ATR values indicate higher market volatility.
🔹 Why is this useful?
Helps traders identify potential breakout or consolidation phases.
Allows better risk management by understanding price fluctuations.
6️⃣ Trend Strength Calculation
The indicator calculates trend strength based on the difference between the EMAs:
A higher trend strength value suggests a stronger directional trend.
Displayed as a percentage for better clarity.
🔹 Why is this useful?
Helps traders differentiate between strong and weak trends.
Reduces the likelihood of entering weak or choppy markets.
7️⃣ OLED-Style Dashboard for Market Data
A futuristic OLED-styled table is used to display critical market data in a visually appealing way:
Trend direction (Bullish/Bearish with an arrow 📈📉).
Current price.
Momentum value.
Strength meters (Bullish/Bearish).
Trend strength percentage.
Volatility Meter
The dashboard uses high-contrast colors and neon glow effects, making it easier to read against dark backgrounds.
🔹 Why is this useful?
Provides a centralized view of key trading metrics.
Eliminates the need to manually calculate trend strength.
8️⃣ Modern Style Neon Glow Effects
To enhance visibility, the indicator applies glowing effects to:
Moving Averages (EMAs): Highlighted with layered glow effects.
Candlesticks: Borders and wicks dynamically change color based on trend direction.
🔹 Why is this useful?
Improves readability in low-contrast or dark-mode charts.
Helps traders spot trends faster without reading numerical data.
9️⃣ Automated Buy & Sell Alerts
The script triggers alerts when momentum crosses key levels:
Above 55 → Potential Long Setup
Below 45 → Potential Short Setup.
🔹 Why is this useful?
Alerts help traders react quickly without constantly monitoring the chart.
Reduces the risk of missing critical trade opportunities.
🔹 Final Summary: Why is This Indicator Useful?
This futuristic cyberpunk-styled trading tool enhances traditional market analysis by combining technical indicators with high-visibility visuals.
🔹 Key Benefits:
✅ Customizable Display – Toggle elements based on trading needs.
✅ Trend Detection – EMAs highlight uptrends & downtrends.
✅ Momentum Tracking – RSI-based momentum gauge identifies strong moves.
✅ Strength Meters – Bullish/Bearish power is clearly visualized.
✅ Volatility Insights – ATR-based metric highlights market turbulence.
✅ Trend Strength Analysis – Quantifies trend intensity.
✅ Dashboard – Provides a centralized, easy-to-read data panel.
✅ Cyberpunk Neon Glow – Enhances clarity with stylish aesthetics.
✅ Real-Time Alerts – Helps traders react to key opportunities.
This indicator is designed to be both functional and visually appealing, making market analysis more intuitive and efficient. 🚀
Trend with ADX/EMA - Buy & Sell SignalsThis script is designed to help traders make buy and sell decisions based on trend analysis using two key methods: ADX (Average Directional Index) and EMA (Exponential Moving Averages). Here's a breakdown in simple terms:
What Does It Do?
Identifies the Trend's Strength and Direction:
Uses the ADX indicator to determine how strong the trend is.
Compares two lines (DI+ and DI−) to identify whether the trend is moving up or down.
Generates Buy and Sell Signals:
Uses two EMAs (a fast one and a slow one) to check when the price crosses key levels, signaling a possible buy or sell opportunity.
Plots visual indicators (arrows and labels) for easy interpretation.
Color-Codes the Chart:
Highlights the background in green when the trend is bullish (uptrend).
Highlights the background in red when the trend is bearish (downtrend).
Alerts the User:
Creates alerts when specific conditions for buying or selling are met.
Key Components:
1. ADX (Trend Strength & Direction)
What is ADX?
ADX measures how strong the trend is (not the direction). Higher ADX means a stronger trend.
It also calculates two lines:
DI+: Measures upward movement strength.
DI−: Measures downward movement strength.
How It Works in the Script:
If DI+ is greater than DI−, it’s a bullish trend (upward).
If DI− is greater than DI+, it’s a bearish trend (downward).
The background turns green for an uptrend and red for a downtrend.
2. EMA (Buy and Sell Decisions)
What is EMA?
EMA is a moving average that gives more weight to recent prices. It’s used to smooth out price fluctuations.
How It Works in the Script:
The script calculates two EMAs:
Fast EMA (short-term average): Reacts quickly to price changes.
Slow EMA (long-term average): Reacts slower and shows overall trends.
When the Fast EMA crosses above the Slow EMA, it’s a signal to Buy.
When the Fast EMA crosses below the Slow EMA, it’s a signal to Sell.
These signals are marked on the chart as "Buy" and "Sell" labels.
3. Buy and Sell Alerts
The script sets up alerts for the user:
Buy Alert: When a crossover indicates a bullish signal.
Sell Alert: When a crossunder indicates a bearish signal.
Visual Elements on the Chart:
Background Colors:
Green: When the DI+ line indicates an uptrend.
Red: When the DI− line indicates a downtrend.
EMA Lines:
Green Line: Fast EMA.
Red Line: Slow EMA.
Buy/Sell Labels:
"Buy" label: Shown when the Fast EMA crosses above the Slow EMA.
"Sell" label: Shown when the Fast EMA crosses below the Slow EMA.
Why Use This Script?
Trend Analysis: Helps you quickly identify the strength and direction of the market trend.
Buy/Sell Signals: Gives clear signals to enter or exit trades based on trend and EMA crossovers.
Custom Alerts: Ensures you never miss a trading opportunity by notifying you when conditions are met.
Visual Simplicity: Makes it easy to interpret trading signals with color-coded backgrounds and labeled arrows.
AuriumFlowAURIUM (GOLD-Weighted Average with Fractal Dynamics)
Aurium is a cutting-edge indicator that blends volume-weighted moving averages (VWMA), fractal geometry, and Fibonacci-inspired calculations to deliver a precise and holistic view of market trends. By dynamically adjusting to price and volume, Aurium uncovers key levels of confluence for trend reversals and continuations, making it a powerful tool for traders.
Key Features:
Dynamic Trendline (GOLD):
The central trendline is a weighted moving average based on price and volume, tuned using Fibonacci-based fast (34) and slow (144) exponential moving average lengths. This ensures the trendline adapts seamlessly to the flow of market dynamics.
Formula:
GOLD = VWMA(34) * Volume Factor + VWMA(144) * (1 - Volume Factor)
Fractal Highs and Lows:
Detects pivotal market points using a fractal lookback period (default 5, odd-numbered). Fractals identify local highs and lows over a defined window, capturing the structure of market cycles.
Trend Background Highlighting:
Bullish Zone: Price above the GOLD line with a green background.
Bearish Zone: Price below the GOLD line with a red background.
Buy and Sell Alerts:
Generates actionable signals when fractals align with GOLD. Bullish fractals confirm continuation or reversal in an uptrend, while bearish fractals validate a downtrend.
The Math Behind Aurium:
Volume-Weighted Adjustments:
By integrating volume into the calculation, Aurium dynamically emphasizes price levels with greater participation, giving traders insight into zones of institutional interest.
Formula:
VWMA = EMA(Close * Volume) / EMA(Volume)
Fractal Calculations:
Fractals are identified as local maxima (highs) or minima (lows) based on the surrounding bars, leveraging the natural symmetry in price behavior.
Fibonacci Relationships:
The 34 and 144 EMA lengths are Fibonacci numbers, offering a natural alignment with price cycles and market rhythms.
Ideal For:
Traders seeking a precise and intuitive indicator for aligning with trends and detecting reversals.
Strategies inspired by Bill Williams, with added volume and fractal-based insights.
Short-term scalpers and long-term trend-followers alike.
Unlock deeper market insights and trade with precision using Aurium!
Smoothed Source Weighted EMAThe Smoothed Source EMA is a tool designed to help traders identify potential buying and selling opportunities in the market. It combines two key elements: price smoothing (using standard deviation) and an Exponential Moving Average (EMA). The purpose is to filter out the day-to-day price fluctuations and create clearer buy and sell signals.
Key Concepts Behind the Indicator:
Price Smoothing (Standard Deviation):
To make the price action easier to follow, the indicator first "smooths" the price. This is done by looking at how much the price tends to move up and down (known as standard deviation).
It then creates two "bands" around the current price—one above and one below. These bands represent a smoothed version of the price and help filter out the noise caused by small, random price movements.
Exponential Moving Average (EMA):
The indicator also uses an Exponential Moving Average (EMA), which is a line that represents the average price over a certain period of time (but gives more weight to recent prices). The EMA helps capture the general trend of the price.
The indicator uses this EMA to compare the current price with the overall trend.
How Does the Indicator Work?
Once the indicator calculates the smoothed price bands and the EMA, it looks for specific conditions to trigger a buy or sell signal:
Long (Buy) Signal:
A buy signal happens when the smoothed price (the lower band) is above the EMA. In simple terms, the price is moving up, and the indicator is telling you it's a good time to buy.
The more "weight" or influence you give to the EMA, the slower this buy signal will appear, meaning it’ll only trigger when there’s a strong enough upward movement.
Short (Sell) Signal:
A sell signal occurs when the smoothed price (the upper band) is below the EMA. This suggests the price is moving down, and the indicator signals that it might be time to sell.
Again, the more "weight" you put on the EMA, the slower the sell signal will appear, as the indicator waits for a clearer downtrend.
Why is this Useful for Traders?
Smoothing the Price: Many traders struggle with the noise of price fluctuations, where the price moves up and down quickly without a clear trend. By smoothing the price, this indicator helps traders focus on the bigger picture and avoid reacting to every small movement.
Clear Buy and Sell Signals: The indicator generates easy-to-understand buy and sell signals based on the relationship between the smoothed price and the EMA. If the price is above the smoothed level and EMA, it’s a signal to buy. If it’s below, it’s a signal to sell.
Customizable Sensitivity: The indicator lets traders adjust how sensitive the buy and sell signals are. By changing certain settings, such as the smoothing length and the weight of the EMA, traders can make the indicator react faster or slower depending on how quickly they want to catch changes in the market.
How the Indicator Appears on the Chart:
EMA Line: A line that represents the trend of the price.
Upper and Lower Smoothed Bands: Two bands above and below the price that help identify when the price is moving up or down relative to the trend.
Buy and Sell Arrows: Small arrows on the chart show where the indicator suggests buying or selling.
Colored Bars: The bars on the chart may change color to visually indicate whether the indicator suggests a buy (green) or a sell (red).
In Summary:
The Smoothed Source EMA helps you identify trends by smoothing out price movements using standard deviation, then comparing these smoothed prices with the Exponential Moving Average (EMA).
When the smoothed price moves above or below the EMA, it gives you a signal: a buy when the smoothed price is above the EMA, and a sell when it’s below.
You can adjust how quickly or slowly these signals appear by modifying the settings, giving you control over how sensitive the indicator is to changes in the market.
This indicator is useful for traders who want to reduce noise and focus on the overall trend, using clear, visually simple signals to guide their trading decisions.
Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
EMA with Supply and Demand Zones
The EMA with Supply and Demand Strategy is a trend-following trading approach that integrates Exponential Moving Averages (EMA) with supply and demand zones to identify potential entry and exit points. Below is a detailed description of its components and logic:
Key Components of the Strategy
1. EMA (Exponential Moving Average)
The EMA is used as a trend filter:
Bullish Trend: Price is above the EMA.
Bearish Trend: Price is below the EMA.
The EMA ensures that trades align with the overall market trend, reducing counter-trend risks.
2. Supply and Demand Zones
Demand Zone:
Represents areas where the price historically found support (buyers dominated).
Calculated using the lowest low over a specified lookback period.
Used for identifying potential long entry points.
Supply Zone:
Represents areas where the price historically faced resistance (sellers dominated).
Calculated using the highest high over a specified lookback period.
Used for identifying potential short entry points.
3. Trade Conditions
Long Trade:
Triggered when:
The price is above the EMA (bullish trend).
The low of the current candle touches or penetrates the most recent demand zone.
Short Trade:
Triggered when:
The price is below the EMA (bearish trend).
The high of the current candle touches or penetrates the most recent supply zone.
4. Exit Conditions
Long Exit:
Exit the trade when the price closes below the EMA, indicating a potential trend reversal.
Short Exit:
Exit the trade when the price closes above the EMA, signaling a potential upward reversal.
Visual Representation
EMA: A blue line plotted on the chart to show the trend.
Supply Zones: Red horizontal lines representing potential resistance levels.
Demand Zones: Green horizontal lines representing potential support levels.
These zones dynamically adjust to reflect the most recent 3 levels.
How the Strategy Works
Trend Identification:
The EMA determines the direction of the trade:
Look for long trades only in a bullish trend (price above EMA).
Look for short trades only in a bearish trend (price below EMA).
Entry Points:
Wait for price interaction with a supply or demand zone:
If the price touches a demand zone during a bullish trend, initiate a long trade.
If the price touches a supply zone during a bearish trend, initiate a short trade.
Risk Management:
The strategy exits trades if the price moves against the trend (crosses the EMA).
This ensures minimal exposure during adverse market movements.
Benefits of the Strategy
Trend Alignment:
Reduces counter-trend trades, improving the win rate.
Clear Entry and Exit Rules:
Combines price action (zones) with a reliable trend filter (EMA).
Dynamic Levels:
The supply and demand zones adapt to changing market conditions.
Customization Options
EMA Length:
Adjust to suit different timeframes or market conditions (e.g., 20 for faster trends, 50 for slower trends).
Lookback Period:
Fine-tune to capture broader or narrower supply and demand zones.
Risk/Reward Preferences:
Pair the strategy with stop-loss and take-profit levels for enhanced control.
This strategy is ideal for traders looking for a structured approach to identify high-probability trades while aligning with the prevailing trend. Backtest and optimize parameters based on your trading style and the specific asset you're tradin
Eze Profit - VWAP + MACD Combined SignalThe Eze Profit - VWAP + MACD Combined Signal is an advanced trading tool designed to help traders align price trends with momentum confirmation for better decision-making. By combining Volume-Weighted Average Price (VWAP) and Moving Average Convergence Divergence (MACD), this indicator provides clear entry and exit signals, allowing traders to follow trends and take advantage of momentum shifts.
How It Works:
VWAP:
VWAP represents the average price of an asset, weighted by volume, over a specific period.
It acts as a dynamic support/resistance level and trend filter. Price above VWAP indicates bullish conditions, while price below VWAP suggests bearish conditions.
MACD:
MACD measures momentum through the difference between fast and slow exponential moving averages (EMAs).
Signals are generated when the MACD line crosses its signal line:
Bullish Crossover: Indicates increasing upward momentum.
Bearish Crossunder: Indicates increasing downward momentum.
Combined Logic:
Long Signal: Triggered when price is above VWAP, and MACD exhibits a bullish crossover.
Short Signal: Triggered when price is below VWAP, and MACD exhibits a bearish crossunder.
The script tracks the trader's "in-position" state to prevent redundant signals and ensure clarity.
How to Use:
Use this script to identify potential long and short trading opportunities:
Buy Signal: Enter a long position when the price moves above VWAP and MACD confirms bullish momentum.
Sell Signal: Exit or short when the price drops below VWAP and MACD confirms bearish momentum.
Combine with additional tools like support/resistance, volume analysis, or candlestick patterns for confirmation.
Features:
VWAP Trend Filter: Dynamically adjusts to the trading session to identify overall trend direction.
MACD Momentum Confirmation: Detects key momentum shifts with configurable settings for fast, slow, and signal lengths.
Position State Tracking: Avoids signal redundancy by monitoring open positions.
Buy/Sell Visualizations: Plots Buy/Sell signals directly on the chart for ease of use.
Alerts: Notifies traders in real-time when a long or short signal is triggered.
Customizable Settings:
MACD Fast Length, Slow Length, and Signal Smoothing parameters.
VWAP timeframe resolution to adapt to different trading styles (e.g., intraday or daily).
Credits:
This script is based on standard VWAP and MACD calculations provided by TradingView’s library and has been enhanced with unique logic for combined signal generation.
Notes:
This indicator is intended for educational purposes and should not be considered financial advice. Use it as part of a broader trading strategy alongside other tools for optimal results.
followerFollower Indicator
This custom Follower Indicator is designed to track market trends and generate buy/sell signals based on price movements and adaptive moving averages. The indicator adjusts dynamically to market conditions using an Exponential Moving Average (EMA) and a smoothed average of the high-low range over the last 20 bars.
Key Features:
Adaptive Trend Following: The indicator uses an EMA of the close price along with a dynamically adjusted range (high-low) to create an adaptive trend-following line.
Buy and Sell Signals: Buy signals are generated when the EMA crosses above the follower line, while sell signals occur when the follower line crosses above the EMA.
Dynamic Color Coding: The indicator line changes color based on the relationship between the price and the follower line. It turns blue when the price is above the follower line and red when the price is below.
Customizable Parameters: Users can adjust the range multiplier (oran) and the EMA period (uzunluk) to fine-tune the indicator to different market conditions.
How to Use:
Buy Signal: A buy signal is triggered when the EMA crosses above the follower line.
Sell Signal: A sell signal is triggered when the follower line crosses above the EMA.
Notes:
This indicator is intended to help identify market trends and potential entry/exit points based on price behavior and momentum.
It is recommended to use this indicator in conjunction with other technical analysis tools and risk management strategies.
Feel free to adjust the parameters based on your trading style and preferences. Happy trading!
Custom V2 KillZone US / FVG / EMAThis indicator is designed for traders looking to analyze liquidity levels, opportunity zones, and the underlying trend across different trading sessions. Inspired by the ICT methodology, this tool combines analysis of Exponential Moving Averages (EMA), session management, and Fair Value Gap (FVG) detection to provide a structured and disciplined approach to trading effectively.
Indicator Features
Identifying the Underlying Trend with Two EMAs
The indicator uses two EMAs on different, customizable timeframes to define the underlying trend:
EMA1 (default set to a daily timeframe): Represents the primary underlying trend.
EMA2 (default set to a 4-hour timeframe): Helps identify secondary corrections or impulses within the main trend.
These two EMAs allow traders to stay aligned with the market trend by prioritizing trades in the direction of the moving averages. For example, if prices are above both EMAs, the trend is bullish, and long trades are favored.
Analysis of Market Sessions
The indicator divides the day into key trading sessions:
Asian Session
London Session
US Pre-Open Session
Liquidity Kill Session
US Kill Zone Session
Each session is represented by high and low zones as well as mid-lines, allowing traders to visualize liquidity levels reached during these periods. Tracking the price levels in different sessions helps determine whether liquidity levels have been "swept" (taken) or not, which is essential for ICT methodology.
Liquidity Signal ("OK" or "STOP")
A specific signal appears at the end of the "Liquidity Kill" session (just before the "US Kill Zone" session):
"OK" Signal: Indicates that liquidity conditions are favorable for trading the "US Kill Zone" session. This means that liquidity levels have been swept in previous sessions (Asian, London, US Pre-Open), and the market is ready for an opportunity.
"STOP" Signal: Indicates that it is not favorable to trade the "US Kill Zone" session, as certain liquidity conditions have not been met.
The "OK" or "STOP" signal is based on an analysis of the high and low levels from previous sessions, allowing traders to ensure that significant liquidity zones have been reached before considering positions in the "Kill Zone".
Detection of Fair Value Gaps (FVG) in the US Kill Zone Session
When an "OK" signal is displayed, the indicator identifies Fair Value Gaps (FVG) during the "US Kill Zone" session. These FVGs are areas where price may return to fill an "imbalance" in the market, making them potential entry points.
Bullish FVG: Detected when there is a bullish imbalance, providing a buying opportunity if conditions align with the underlying trend.
Bearish FVG: Detected when there is a bearish imbalance, providing a selling opportunity in the trend direction.
FVG detection aligns with the ICT Silver Bullet methodology, where these imbalance zones serve as probable entry points during the "US Kill Zone".
How to Use This Indicator
Check the Underlying Trend
Before trading, observe the two EMAs (daily and 4-hour) to understand the general market trend. Trades will be prioritized in the direction indicated by these EMAs.
Monitor Liquidity Signals After the Asian, London, and US Pre-Open Sessions
The high and low levels of each session help determine if liquidity has already been swept in these areas. At the end of the "Liquidity Kill" session, an "OK" or "STOP" label will appear:
"OK" means you can look for trading opportunities in the "US Kill Zone" session.
"STOP" means it is preferable not to take trades in the "US Kill Zone" session.
Look for Opportunities in the US Kill Zone if the Signal is "OK"
When the "OK" label is present, focus on the "US Kill Zone" session. Use the Fair Value Gaps (FVG) as potential entry points for trades based on the ICT methodology. The identified FVGs will appear as colored boxes (bullish or bearish) during this session.
Use ICT Methodology to Manage Your Trades
Follow the FVGs as potential reversal zones in the direction of the trend, and manage your positions according to your personal strategy and the rules of the ICT Silver Bullet method.
Customizable Settings
The indicator includes several customization options to suit the trader's preferences:
EMA: Length, source (close, open, etc.), and timeframe.
Market Sessions: Ability to enable or disable each session, with color and line width settings.
Liquidity Signals: Customization of colors for the "OK" and "STOP" labels.
FVG: Option to display FVGs or not, with customizable colors for bullish and bearish FVGs, and the number of bars for FVG extension.
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Cet indicateur est conçu pour les traders souhaitant analyser les niveaux de liquidité, les zones d’opportunité, et la tendance de fond à travers différentes sessions de trading. Inspiré de la méthodologie ICT, cet outil combine l'analyse des moyennes mobiles exponentielles (EMA), la gestion des sessions de marché, et la détection des Fair Value Gaps (FVG), afin de fournir une approche structurée et disciplinée pour trader efficacement.
Machine Learning RSI [BackQuant]Machine Learning RSI
The Machine Learning RSI is a cutting-edge trading indicator that combines the power of Relative Strength Index (RSI) with Machine Learning (ML) clustering techniques to dynamically determine overbought and oversold thresholds. This advanced indicator adapts to market conditions in real-time, offering traders a robust tool for identifying optimal entry and exit points with increased precision.
Core Concept: Relative Strength Index (RSI)
The RSI is a well-known momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Typically, RSI values above 70 are considered overbought, and values below 30 are considered oversold. However, static thresholds may not be effective in all market conditions.
This script enhances the RSI by integrating a dynamic thresholding system powered by Machine Learning clustering, allowing it to adapt thresholds based on historical RSI behavior and market context.
Machine Learning Clustering for Dynamic Thresholds
The Machine Learning (ML) component uses clustering to calculate dynamic thresholds for overbought and oversold levels. Instead of relying on fixed RSI levels, this indicator clusters historical RSI values into three groups using a percentile-based initialization and iterative optimization:
Cluster 1: Represents lower RSI values (typically associated with oversold conditions).
Cluster 2: Represents mid-range RSI values.
Cluster 3: Represents higher RSI values (typically associated with overbought conditions).
Dynamic thresholds are determined as follows:
Long Threshold: The upper centroid value of Cluster 3.
Short Threshold: The lower centroid value of Cluster 1.
This approach ensures that the indicator adapts to the current market regime, providing more accurate signals in volatile or trending conditions.
Smoothing Options for RSI
To further enhance the effectiveness of the RSI, this script allows traders to apply various smoothing methods to the RSI calculation, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Hull Moving Average (HMA)
Linear Regression (LINREG)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Adaptive Linear Moving Average (ALMA)
T3 Moving Average
Traders can select their preferred smoothing method and adjust the smoothing period to suit their trading style and market conditions. The option to smooth the RSI reduces noise and makes the indicator more reliable for detecting trends and reversals.
Long and Short Signals
The indicator generates long and short signals based on the relationship between the RSI value and the dynamic thresholds:
Long Signals: Triggered when the RSI crosses above the long threshold, signaling bullish momentum.
Short Signals: Triggered when the RSI falls below the short threshold, signaling bearish momentum.
These signals are dynamically adjusted to reflect real-time market conditions, making them more robust than static RSI signals.
Visualization and Clustering Insights
The Machine Learning RSI provides an intuitive and visually rich interface, including:
RSI Line: Plotted in real-time, color-coded based on its position relative to the dynamic thresholds (green for long, red for short, gray for neutral).
Dynamic Threshold Lines: The script plots the long and short thresholds calculated by the ML clustering process, providing a clear visual reference for overbought and oversold levels.
Cluster Plots: Each RSI cluster is displayed with distinct colors (green, orange, and red) to give traders insights into how RSI values are grouped and how the dynamic thresholds are derived.
Customization Options
The Machine Learning RSI is highly customizable, allowing traders to tailor the indicator to their preferences:
RSI Settings : Adjust the RSI length, source price, and smoothing method to match your trading strategy.
Threshold Settings : Define the range and step size for clustering thresholds, allowing you to fine-tune the clustering process.
Optimization Settings : Control the performance memory, maximum clustering steps, and maximum data points for ML calculations to ensure optimal performance.
UI Settings : Customize the appearance of the RSI plot, dynamic thresholds, and cluster plots. Traders can also enable or disable candle coloring based on trend direction.
Alerts and Automation
To assist traders in staying on top of market movements, the script includes alert conditions for key events:
Long Signal: When the RSI crosses above the long threshold.
Short Signal: When the RSI crosses below the short threshold.
These alerts can be configured to notify traders in real-time, enabling timely decisions without constant chart monitoring.
Trading Applications
The Machine Learning RSI is versatile and can be applied to various trading strategies, including:
Trend Following: By dynamically adjusting thresholds, this indicator is effective in identifying and following trends in real-time.
Reversal Trading: The ML clustering process helps identify extreme RSI levels, offering reliable signals for reversals.
Range-Bound Trading: The dynamic thresholds adapt to market conditions, making the indicator suitable for trading in sideways markets where static thresholds often fail.
Final Thoughts
The Machine Learning RSI represents a significant advancement in RSI-based trading indicators. By integrating Machine Learning clustering techniques, this script overcomes the limitations of static thresholds, providing dynamic, adaptive signals that respond to market conditions in real-time. With its robust visualization, customizable settings, and alert capabilities, this indicator is a powerful tool for traders seeking to enhance their momentum analysis and improve decision-making.
As always, thorough backtesting and integration into a broader trading strategy are recommended to maximize the effectiveness!
Volume Based Price Prediction [EdgeTerminal]This indicator combines price action, volume analysis, and trend prediction to forecast potential future price movements. The indicator creates a dynamic prediction zone with confidence bands, helping you visualize possible price trajectories based on current market conditions.
Key Features
Dynamic price prediction based on volume-weighted trend analysis
Confidence bands showing potential price ranges
Volume-based candle coloring for enhanced market insight
VWAP and Moving Average overlay
Customizable prediction parameters
Real-time updates with each new bar
Technical Components:
Volume-Price Correlation: The indicator analyzes the relationship between price movements and volume, Identifies stronger trends through volume confirmation and uses Volume-Weighted Average Price (VWAP) for price equilibrium
Trend Strength Analysis: Calculates trend direction using exponential moving averages, weights trend strength by relative volume and incorporates momentum for improved accuracy
Prediction Algorithm: combines current price, trend, and volume metrics, projects future price levels using weighted factors and generates confidence bands based on price volatility
Customizable Parameters:
Moving Average Length: Controls the smoothing period for calculations
Volume Weight Factor: Adjusts how much volume influences predictions
Prediction Periods: Number of bars to project into the future
Confidence Band Width: Controls the width of prediction bands
How to use it:
Look for strong volume confirmation with green candles, watch for prediction line slope changes, use confidence bands to gauge potential volatility and compare predictions with key support/resistance levels
Some useful tips:
Start with default settings and adjust gradually
Use wider confidence bands in volatile markets
Consider prediction lines as zones rather than exact levels
Best applications of this indicator:
Trend continuation probability assessment
Potential reversal point identification
Risk management through confidence bands
Volume-based trend confirmation
EMA Distance & Sector InfoThis indicator provides insights into price trends relative to Exponential Moving Averages (EMAs) and displays sector/industry information about the asset. Below is a detailed explanation of its purpose and what it is designed to achieve:
Purpose of the Code
The indicator offers two key functionalities:
1. Analyzing Price Distance from Multiple EMAs:
• Helps traders understand how far the current price is from key EMAs, expressed as a percentage.
• Calculates average percentage distances over a specified period (default: 63 days) to spot consistent trends or mean reversion opportunities.
• Useful for trend-following strategies, allowing the trader to see when the price is above or below important EMAs (e.g., 9, 21, 50, 100, and 150-period EMAs).
2. Displaying Asset Sector and Industry Information:
• Displays the sector and industry of the asset being analyzed (e.g., Technology, Consumer Goods).
• Provides additional context when evaluating performance across a specific sector or comparing an asset to its peers.
Who Would Use This Indicator?
This indicator is particularly helpful for:
1. Swing Traders and Positional Traders:
• They can use it to track whether the price is trading significantly above or below critical EMAs, which often signals overbought/oversold conditions or trend strength.
• The average percentage distances help to identify momentum shifts or pullback opportunities.
2. Sector/Industry-Focused Investors:
• Understanding an asset’s sector and industry helps investors gauge how the asset fits into the broader market context.
• This is valuable for sector rotation strategies, where investors shift funds between sectors based on performance trends.
How It Helps in Trading Decisions
1. Entry and Exit Points:
• If the price is far above an EMA (e.g., 21 EMA), it might indicate an overbought condition or a strong trend, while a negative percentage could signal a pullback or reversal opportunity.
• The average percentage distances smooth the fluctuations and reveal longer-term trends.
2. Contextual Information:
• Knowing the sector and industry is useful when analyzing trends. For example, if Technology stocks are doing well, and this asset belongs to that sector, it could indicate sector-wide momentum.
Summary of the Indicator’s Purpose
This code provides:
• EMA trend monitoring: Visualizes the price position relative to multiple EMAs and averages those distances for smoother insights.
• Sector and industry information: Adds valuable context for asset performance analysis.
• Decision-making support: Helps traders identify overbought/oversold levels and assess the asset within the broader market landscape.
In essence, this indicator is a multi-purpose tool that combines technical analysis (through EMA distances) with fundamental context (via sector/industry info), making it valuable for traders and investors aiming to time entries/exits or understand market behavior better.
Gold Scalping Strategy with Precise EntriesThe Gold Scalping Strategy with Precise Entries is designed to take advantage of short-term price movements in the gold market (XAU/USD). This strategy uses a combination of technical indicators and chart patterns to identify precise buy and sell opportunities during times of consolidation and trend continuation.
Key Elements of the Strategy:
Exponential Moving Averages (EMAs):
50 EMA: Used as the shorter-term moving average to detect the recent price trend.
200 EMA: Used as the longer-term moving average to determine the overall market trend.
Trend Identification:
A bullish trend is identified when the 50 EMA is above the 200 EMA.
A bearish trend is identified when the 50 EMA is below the 200 EMA.
Average True Range (ATR):
ATR (14) is used to calculate the market's volatility and to set a dynamic stop loss based on recent price movements. Higher ATR values indicate higher volatility.
ATR helps define a suitable stop-loss distance from the entry point.
Relative Strength Index (RSI):
RSI (14) is used as a momentum oscillator to detect overbought or oversold conditions.
However, in this strategy, the RSI is primarily used as a consolidation filter to look for neutral zones (between 45 and 55), which may indicate a potential breakout or trend continuation after a consolidation phase.
Engulfing Patterns:
Bullish Engulfing: A bullish signal is generated when the current candle fully engulfs the previous bearish candle, indicating potential upward momentum.
Bearish Engulfing: A bearish signal is generated when the current candle fully engulfs the previous bullish candle, signaling potential downward momentum.
Precise Entry Conditions:
Long (Buy):
The 50 EMA is above the 200 EMA (bullish trend).
The RSI is between 45 and 55 (neutral/consolidation zone).
A bullish engulfing pattern occurs.
The price closes above the 50 EMA.
Short (Sell):
The 50 EMA is below the 200 EMA (bearish trend).
The RSI is between 45 and 55 (neutral/consolidation zone).
A bearish engulfing pattern occurs.
The price closes below the 50 EMA.
Take Profit and Stop Loss:
Take Profit: A fixed 20-pip target (where 1 pip = 0.10 movement in gold) is used for each trade.
Stop Loss: The stop-loss is dynamically set based on the ATR, ensuring that it adapts to current market volatility.
Visual Signals:
Buy and sell signals are visually plotted on the chart using green and red labels, indicating precise points of entry.
Advantages of This Strategy:
Trend Alignment: The strategy ensures that trades are taken in the direction of the overall trend, as indicated by the 50 and 200 EMAs.
Volatility Adaptation: The use of ATR allows the stop loss to adapt to the current market conditions, reducing the risk of premature exits in volatile markets.
Precise Entries: The combination of engulfing patterns and the neutral RSI zone provides a high-probability entry signal that captures momentum after consolidation.
Quick Scalping: With a fixed 20-pip profit target, the strategy is designed to capture small price movements quickly, which is ideal for scalping.
This strategy can be applied to lower timeframes (such as 1-minute, 5-minute, or 15-minute charts) for frequent trade opportunities in gold trading, making it suitable for day traders or scalpers. However, proper risk management should always be used due to the inherent volatility of gold.
XAU/USD Strategy with Correct ADX and Bollinger Bands Fill1. *Indicators Used*:
- *Exponential Moving Averages (EMAs)*: Two EMAs (20-period and 50-period) are used to identify the trend direction and potential entry points based on crossovers.
- *Relative Strength Index (RSI)*: A momentum oscillator that measures the speed and change of price movements. It identifies overbought and oversold conditions.
- *Bollinger Bands*: These consist of a middle line (simple moving average) and two outer bands (standard deviations away from the middle). They help to identify price volatility and potential reversal points.
- *Average Directional Index (ADX)*: This indicator quantifies trend strength. It's derived from the Directional Movement Index (DMI) and helps confirm the presence of a strong trend.
- *Average True Range (ATR)*: Used to calculate position size based on volatility, ensuring that trades align with the trader's risk tolerance.
2. *Entry Conditions*:
- *Long Entry*:
- The 20 EMA crosses above the 50 EMA (indicating a potential bullish trend).
- The RSI is below the oversold level (30), suggesting the asset may be undervalued.
- The price is below the lower Bollinger Band, indicating potential price reversal.
- The ADX is above a specified threshold (25), confirming that there is sufficient trend strength.
- *Short Entry*:
- The 20 EMA crosses below the 50 EMA (indicating a potential bearish trend).
- The RSI is above the overbought level (70), suggesting the asset may be overvalued.
- The price is above the upper Bollinger Band, indicating potential price reversal.
- The ADX is above the specified threshold (25), confirming trend strength.
3. *Position Sizing*:
- The script calculates the position size dynamically based on the trader's risk per trade (expressed as a percentage of the total capital) and the ATR. This ensures that the trader does not risk more than the specified percentage on any single trade, adjusting the position size according to market volatility.
4. *Exit Conditions*:
- The strategy uses a trailing stop-loss mechanism to secure profits as the price moves in the trader's favor. The trailing stop is set at a percentage (1.5% by default) below the highest price reached since entry for long positions and above the lowest price for short positions.
- Additionally, if the RSI crosses back above the overbought level while in a long position or below the oversold level while in a short position, the position is closed to prevent losses.
5. *Alerts*:
- Alerts are set to notify the trader when a buy or sell condition is met based on the strategy's rules. This allows for timely execution of trades.
### Summary
This strategy aims to capture significant price movements in the XAU/USD market by combining trend-following (EMAs, ADX) and momentum indicators (RSI, Bollinger Bands). The dynamic position sizing based on ATR helps manage risk effectively. By implementing trailing stops and alert mechanisms, the strategy enhances the trader's ability to act quickly on opportunities while mitigating potential losses.
Precision Cloud by Dr ABIRAM SIVPRASAD
Precision Cloud by Dr. Abhiram Sivprasad"
The " Precision Cloud" script, created by Dr. Abhiram Sivprasad, is a multi-purpose technical analysis tool designed for Forex, Bitcoin, Commodities, Stocks, and Options trading. It focuses on identifying key levels of support and resistance, combined with moving averages (EMAs) and central pivot ranges (CPR), to help traders make informed trading decisions. The script also provides a visual "light system" to highlight potential long or short positions, aiding traders in entering trades with a clear strategy.
Key Features of the Script:
Central Pivot Range (CPR):
The CPR is calculated as the average of the high, low, and close of the price, while the top and bottom pivots are derived from it. These act as dynamic support and resistance zones.
The script can plot daily CPR, support, and resistance levels (S1/R1, S2/R2, S3/R3) as well as optional weekly and monthly pivot points.
The CPR helps identify whether the price is in a bullish, bearish, or neutral zone.
Support and Resistance Levels:
Three daily support (S1, S2, S3) and resistance (R1, R2, R3) levels are plotted based on the CPR.
These levels act as potential reversal or breakout points, allowing traders to make decisions around key price points.
EMA (Exponential Moving Averages):
The script includes two customizable EMAs (default periods of 9 and 21). You can choose the source for these EMAs (open, high, low, or close).
The crossovers between EMA1 and EMA2 help identify potential trend reversals or momentum shifts.
Lagging Span:
The Lagging Span is plotted with a customizable displacement (default 26), which helps identify overall trend direction by comparing past price with the current price.
Light System:
A color-coded table provides a visual representation of market conditions:
Green indicates bullish signals (e.g., price above CPR, EMAs aligning positively).
Red indicates bearish signals (e.g., price below CPR, EMAs aligning negatively).
Yellow indicates neutral conditions, where there is no clear trend direction.
The system includes lights for CPR, EMA, Long Position, and Short Position, helping traders quickly assess whether the market is in a buying or selling opportunity.
Trading Strategies Using the Script
1. Forex Trading:
Trend-Following with EMAs: Use the EMA crossovers to capture trending markets in Forex. A green light for the EMA combined with a price above the daily or weekly pivot levels suggests a buying opportunity. Conversely, if the EMA light turns red and price falls below the CPR levels, look for shorting opportunities.
Reversal Strategy: Watch for price action near the daily S1/R1 levels. If price holds above S1 and the EMA is green, this could signal a reversal from support. The same applies to resistance levels.
2. Bitcoin Trading:
Momentum Breakouts: Bitcoin is known for its sharp moves. The script helps to identify breakouts from the CPR range. If the price breaks above the TC (Top Central Pivot) with bullish EMA alignment (green light), it could signal a strong uptrend.
Lagging Span Confirmation: Use the Lagging Span to confirm the trend direction. For Bitcoin's volatility, when the lagging span shows consistent alignment with the price and CPR, it often indicates continuation of the trend.
3. Commodities Trading:
Support/Resistance Bounce: Commodities such as gold and oil often react well to pivot levels. Look for price bouncing off S1 or R1 for potential entry points. A green CPR light along with price above the pivot range supports a bullish bias.
EMA Pullback Strategy: If price moves in a strong trend and pulls back to one of the EMAs, a green EMA light suggests re-entry on a pullback. If the EMA light is red and price breaks below the BC (Bottom Central Pivot), short positions could be considered.
4. Stocks Trading:
Long Position Strategy: For stocks, use the combination of the long position light turning green (price above TC and EMA alignment) as a signal to buy. This could be especially useful for riding bullish trends in growth stocks or during earnings seasons when volatility is high.
Short Position Strategy: If the short position light turns green, indicating price below BC and EMAs turning bearish, this could be an ideal setup for shorting overvalued stocks or during market corrections.
5. Options Trading:
Directional Bias for Options: The light system is particularly helpful for options traders. A green long position light provides a clear signal to buy call options, while a green short position light supports buying puts.
Pivot Breakout Strategy: Buy options (calls or puts) when the price breaks above resistance or below support, with confirmation from the CPR and EMA lights. This helps capture the sharp moves required for profitable options trades.
Conclusion
The S&R Precision Cloud script is a versatile tool for traders across markets, including Forex, Bitcoin, Commodities, Stocks, and Options. It combines critical technical elements like pivot ranges, support and resistance levels, EMAs, and the Lagging Span to provide a clear picture of market conditions. The intuitive light system helps traders quickly assess whether to take a long or short position, making it an excellent tool for both new and experienced traders.
The S&R Precision Cloud by Dr. Abhiram Sivprasad script is a technical analysis tool designed to assist traders in making informed decisions. However, it should not be interpreted as financial or investment advice. The signals generated by the script are based on historical price data and technical indicators, which are inherently subject to market fluctuations and do not guarantee future performance.
Trading in Forex, Bitcoin, Commodities, Stocks, and Options carries a high level of risk and may not be suitable for all investors. You should be aware of the risks involved and be willing to accept them before engaging in such activities. Always conduct your own research and consult with a licensed financial advisor or professional before making any trading decisions.
The creators of this script are not responsible for any financial losses that may occur from its use. Past performance is not indicative of future results, and the use of this script is at your own risk.
Bullish Gap Up DetectionThis indicator is designed to identify gap-up trading opportunities in real-time. A gap-up occurs when the opening price of a stock is higher than the previous day's high, signaling potential bullish momentum.
Key Features :
Gap Detection : The indicator detects when today’s open is above yesterday’s high and remains above that level throughout the trading session.
Visual Alerts : A triangle shape appears below the price bar when a gap-up condition is met, providing clear visual signals for traders to consider potential entry points.
EMA Analysis : The indicator incorporates two Exponential Moving Averages:
10-day EMA: Used to assess short-term price trends and help determine if the stock is currently in an upward momentum phase.
20-day EMA: Provides additional context for medium-term trends, ensuring that gaps are only considered when the stock is in a favorable trend.
The indicator confirms that the 10-day EMA is above the 20-day EMA, indicating bullish sentiment in the market.
This indicator can be used in various trading strategies to capitalize on momentum following gap-up openings. It’s suitable for day traders and swing traders looking for entry points in trending stocks.
EMA14 Second Time BUY/SELL AlertsEMA14 Crossover Strategy with Conditional BUY/SELL Alerts
This powerful script provides dynamic BUY and SELL alerts based on the interaction between price action and the EMA14 (Exponential Moving Average 14). Ideal for traders looking to capitalize on trend reversals and breakout patterns, this indicator helps you time entries and exits with precision.
Key Features:
Second-Time Crossover Alerts: The script tracks when the price crosses the EMA14 for the second time. This adds confirmation to price movements and helps filter out false signals.
Conditional BUY/SELL Alerts:
BUY Alert: Triggered when the price closes above the EMA14 after a previous SELL signal, indicating a potential trend reversal or breakout to the upside.
SELL Alert: Triggered when the price closes below the EMA14 after a previous BUY signal, signaling a possible shift to the downside.
Advanced Crossover Tracking:
The script counts each crossover of the price relative to the EMA14, generating a BUY or SELL signal on the second instance to provide additional confirmation of trend strength.
Visual Alerts: Labels are plotted directly on the chart to highlight when a BUY or SELL signal has occurred, providing immediate visual feedback for traders to react in real-time.
How It Works:
The script combines the simplicity of EMA14 with enhanced logic that tracks both crossovers and closes relative to the moving average. This ensures that the signals are based not only on quick movements but also on price confirmation, reducing noise and false breakouts.
This script is perfect for traders who rely on moving average strategies and want additional filtering to confirm trends and optimize trade timing.
Median Standard Deviation | viResearchMedian Standard Deviation | viResearch
The "Median Standard Deviation" indicator, developed by viResearch, introduces a unique combination of median smoothing and standard deviation to detect trends and volatility in market data. This tool provides traders with a stable and accurate measure of price trends by integrating median smoothing with a customized calculation of the standard deviation. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation:
The "Median Standard Deviation" indicator incorporates median smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
Median Smoothing:
DEMA Calculation (len_dema): The script applies a Double Exponential Moving Average (DEMA) to smooth the price data over a user-defined period, reducing noise and helping traders focus on broader market trends.
Median Calculation (median_len): The smoothed DEMA data is further refined by calculating the 50th percentile (median) over a specified length, ensuring that the central tendency of price data is captured more accurately than with a simple moving average.
Volatility Measurement:
ATR Calculation (atr_len, atr_mul): The script incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the median, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Analysis:
Standard Deviation Calculation (len_sd): The script calculates the standard deviation of the median over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (sdd, sdl) act as additional indicators of price extremes.
Trend Detection:
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands are used to signal potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs:
The "Median Standard Deviation" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
DEMA Length: Allows traders to adjust the sensitivity of the DEMA smoothing to control the amount of noise filtered from the price data.
Median Length: Users can define the length over which the median price is calculated, providing flexibility in capturing short-term or long-term trends.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing for further customization in detecting price volatility.
Practical Applications:
The "Median Standard Deviation" indicator is particularly effective in volatile markets where price swings can lead to false signals using traditional methods. By combining median smoothing and standard deviation, this tool provides a more robust analysis of trends and price movements.
Key Uses:
Trend Following: The upper and lower bands provide clear signals for entering and exiting trades based on whether the price is moving outside the calculated ranges.
Volatility Detection: The integration of ATR and standard deviation bands allows traders to assess market volatility in real time, enabling more informed trading decisions.
Noise Reduction: The use of median smoothing ensures that short-term price fluctuations do not interfere with broader trend analysis, making this indicator ideal for traders looking to avoid whipsaws in volatile markets.
Advantages and Strategic Value:
The "Median Standard Deviation" indicator offers several key advantages:
Precision in Trend Detection: The combination of median smoothing and standard deviation allows traders to detect trends with greater accuracy, reducing the risk of false signals.
Customization: With several adjustable parameters, traders can fine-tune the indicator to suit different timeframes and trading strategies.
Volatility Sensitivity: By incorporating ATR and standard deviation, this indicator provides an adaptive measure of market volatility, ensuring that traders are always aware of potential price swings.
Summary and Usage Tips:
The "Median Standard Deviation" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of median smoothing and standard deviation provides a nuanced view of market movements, helping traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs, whether used for trend detection, volatility analysis, or noise reduction. The "Median Standard Deviation" offers a reliable and adaptable solution for modern trading strategies.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
Uptrick: Adaptive Cloud Oscillator (ACO)### **Uptrick: Adaptive Cloud Oscillator (ACO)**
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### Introduction
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is an advanced technical analysis tool designed to empower traders with precise trend detection and visual clarity in dynamic market conditions. By seamlessly integrating adaptive trend analysis, volatility filtering, and cloud-based support and resistance levels, the ACO provides traders with the actionable insights needed to navigate complex markets with confidence.
This indicator is highly customizable, allowing traders to tailor its functionality to their specific trading style and preferences. Whether you're a trend follower, swing trader, or looking to identify key support and resistance zones, the **Uptrick: ACO** is an indispensable tool that can adapt to a variety of market conditions.
### Indicator Purpose and Functionality
#### 1. **Adaptive Trend Detection**
At the heart of the **Uptrick: ACO** lies its adaptive trend detection algorithm. Unlike traditional moving averages that may lag in volatile markets or react too slowly to rapid changes, this adaptive method uses a smoothing technique that dynamically adjusts based on market conditions. By doing so, it provides a more responsive trend line that captures meaningful price movements while filtering out minor fluctuations.
- **How It Works:** The trend line is calculated using an adaptive smoothing factor, making it responsive to recent price actions while maintaining a level of stability that prevents whipsaw signals. This ensures that traders are always in tune with the prevailing market trend, whether bullish, bearish, or neutral.
#### 2. **Dynamic Cloud Support and Resistance**
The **Uptrick: ACO** features a dynamic "cloud" that serves as a key element in its analysis. This cloud is constructed using a moving average combined with the Average True Range (ATR), which adjusts based on the market’s volatility. The cloud provides dynamic support and resistance levels, essential for identifying potential reversal zones or confirming trend continuations.
- **Cloud Displacement:** The cloud is displaced forward by a user-defined number of bars, offering a predictive view of where future support and resistance levels may lie. This forward-looking feature helps traders anticipate potential price movements, making the ACO a powerful tool for planning trades ahead of time.
#### 3. **Versatile Visualization Options**
The **Uptrick: ACO** is designed with flexibility in mind, allowing users to choose between two distinct display modes:
- **Buy/Sell Signals:** In this mode, the indicator generates clear buy and sell signals based on crossovers of the trend line and the cloud boundaries. These signals are visualized directly on the chart with up and down labels, making it easy for traders to identify potential entry and exit points.
- **Cloud Fill Only:** For traders who prefer a cleaner chart, this mode removes the buy/sell signals and instead focuses on coloring the area between the upper and lower cloud boundaries. The color of the cloud fill changes based on the trend direction, providing a visual representation of the market's momentum.
- **Optional EMA Line:** An Exponential Moving Average (EMA) line can be optionally displayed on the chart. The EMA serves as an additional trend filter, helping traders further refine their entries and exits. The length, color, and thickness of the EMA are fully customizable to fit individual trading strategies.
### Practical Applications
#### 1. **Trend Following and Reversals**
The **Uptrick: ACO** excels in identifying and following trends. By analyzing the relationship between the trend line and the cloud, traders can determine the strength and direction of the current market trend. The cloud’s dynamic nature means it can adapt to both trending and ranging markets, providing consistent insights regardless of market conditions.
- **Example:** If the trend line crosses above the upper cloud boundary, it signals a potential buy opportunity. Conversely, a cross below the lower cloud boundary suggests a sell opportunity. Traders can use these signals to enter trades aligned with the prevailing trend.
#### 2. **Support and Resistance Identification**
The forward-displaced cloud acts as a predictive support and resistance zone. Traders can use these zones to set stop-loss levels, determine take-profit targets, or identify potential reversal points.
- **Example:** When the price approaches the upper cloud boundary from below, the boundary may act as resistance, indicating a potential reversal or pullback. If the price breaks through this level, it may signal a continuation of the bullish trend.
#### 3. **Volatility-Based Analysis**
By incorporating ATR into its calculations, the **Uptrick: ACO** provides a built-in mechanism to adapt to varying levels of market volatility. This makes it particularly useful in markets prone to sudden spikes in volatility, such as during major economic announcements or geopolitical events.
- **Example:** In a high-volatility environment, the cloud widens, allowing for greater price fluctuations within the trend. Traders can use this information to adjust their risk management strategies, such as widening stop-loss levels during volatile periods to avoid being stopped out prematurely.
### Customization and Flexibility
The **Uptrick: ACO** is designed to be highly customizable, ensuring it can meet the needs of traders with different strategies and preferences. Key customization options include:
- **Cloud and Trend Settings:** Traders can adjust the length of the cloud, the smoothing factor for the trend line, and the displacement of the cloud to optimize the indicator for their specific market and timeframe.
- **Display Modes:** With a simple dropdown selection, traders can choose whether to display buy/sell signals or focus solely on the cloud fill, providing flexibility in how the indicator is visualized.
- **Color and Style Customization:** The colors for bullish and bearish trends, cloud fill, buy/sell signals, and the EMA line can all be customized, allowing traders to integrate the **Uptrick: ACO** seamlessly into their existing chart setups.
### Conclusion
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is more than just a trend indicator—it's a comprehensive market analysis tool that provides traders with a deep understanding of market dynamics. Its combination of adaptive trend analysis, dynamic support and resistance levels, and versatile visualization options makes it an essential tool for traders looking to gain an edge in any market environment.
Whether you're a seasoned trader or just starting, the **Uptrick: ACO** offers the insights and flexibility needed to make informed trading decisions. By helping you identify trends, anticipate reversals, and adapt to changing market conditions, the **Uptrick: ACO** can significantly enhance your trading strategy and improve your overall trading performance.
GannLSVZO Indicator [Algo Alert]The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and Exits (orange X) and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swings and the Gan swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
