Key Intraday Range Analysis - K.I.R.A. The KIRA Indicator is a unique tool designed to provide traders with actionable insights by identifying and analyzing key intraday price ranges. Built upon a specialized methodology, it uses Fibonacci-derived levels anchored to significant opening ranges to generate trading levels for the day. Unlike other indicators that focus on broader trend analysis, KIRA’s approach provides precision, simplicity, and adaptability for intraday traders.
How It Works
KIRA takes the first 30-second range of the European market open and calculates Fibonacci projections derived solely from the golden ratio. These projections form potential areas of interest, such as support and resistance levels, that guide traders in their decision-making process.
By visualizing these levels directly on the chart, KIRA simplifies intraday trading, helping traders identify key reaction zones with high clarity.
Key Features:
-Clean and Readable Output: Generates easily identifiable levels directly on a clear chart to reduce visual clutter.
-Dynamic and Adaptive: Works across various assets, including indices, forex, and commodities, while maintaining reliability on lower timeframes.
How to Use
1. Set Up: Ensure your chart timeframe is aligned with intraday trading, ideally 1-minute or 5-minute intervals.
2. Monitor Levels: Observe how price reacts to the projected levels generated from the opening range.
3. Strategize: Use these levels as potential entries, exits, or areas to tighten risk management, depending on price action.
Unlike conventional indicators that reuse public domain methodologies or classic technical analysis tools, KIRA is based on a nuanced approach to anchoring Fibonacci projections. Its uniqueness lies in its precise application of golden ratio derivatives, specifically tailored to intraday price movements.
The chart accompanying this script provides a clean visualization of the KIRA levels applied to a 1-minute chart of . All outputs are directly from the KIRA script to ensure clarity and ease of use.
Forecasting
Normalized Price ComparisonNormalized Price Comparison Indicator Description
The "Normalized Price Comparison" indicator is designed to provide traders with a visual tool for comparing the price movements of up to three different financial instruments on a common scale, despite their potentially different price ranges. Here's how it works:
Features:
Normalization: This indicator normalizes the closing prices of each symbol to a scale between 0 and 1 over a user-defined period. This normalization process allows for the comparison of price trends regardless of the absolute price levels, making it easier to spot relative movements and trends.
Crossing Alert: It features an alert functionality that triggers when the normalized price lines of the first two symbols (Symbol 1 and Symbol 2) cross each other. This can be particularly useful for identifying potential trading opportunities when one asset's relative performance changes against another.
Customization: Users can input up to three symbols for analysis. The normalization period can be adjusted, allowing flexibility in how historical data is considered for the scaling process. This period determines how many past bars are used to calculate the minimum and maximum prices for normalization.
Visual Representation: The indicator plots these normalized prices in a separate pane below the main chart. Each symbol's normalized price is represented by a distinct colored line:
Symbol 1: Blue line
Symbol 2: Red line
Symbol 3: Green line
Use Cases:
Relative Performance Analysis: Ideal for investors or traders who want to compare how different assets are performing relative to each other over time, without the distraction of absolute price differences.
Divergence Detection: Useful for spotting divergences where one asset might be outperforming or underperforming compared to others, potentially signaling changes in market trends or investment opportunities.
Crossing Strategy: The alert for when Symbol 1 and Symbol 2's normalized lines cross can be used as a part of a trading strategy, signaling potential entry or exit points based on relative price movements.
Limitations:
Static Alert Messages: Due to Pine Script's constraints, the alert messages cannot dynamically include the names of the symbols being compared. The alert will always mention "Symbol 1" and "Symbol 2" crossing.
Performance: Depending on the timeframe and the number of symbols, performance might be affected, especially on lower timeframes with high data frequency.
This indicator is particularly beneficial for those interested in multi-asset analysis, offering a streamlined way to observe and react to relative price movements in a visually coherent manner. It's a powerful tool for enhancing your trading or investment analysis by focusing on trends and relationships rather than raw price data.
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Poisson Projection of Price Levels### **Poisson Projection of Price Levels**
**Overview:**
The *Poisson Projection of Price Levels* is a cutting-edge technical indicator designed to identify and visualize potential support and resistance levels based on historical price interactions. By leveraging the Poisson distribution, this tool dynamically adjusts the significance of each price level's past "touches" to project future interactions with varying degrees of probability. This probabilistic approach offers traders a nuanced view of where price levels may hold or react in upcoming bars, enhancing both analysis and trading strategies.
---
**🔍 **Math & Methodology**
1. **Strata Levels:**
- **Definition:** Strata are horizontal lines spaced evenly around the current closing price.
- **Calculation:**
\
where \(i\) ranges from 0 to \(\text{Strata Count} - 1\).
2. **Forecast Iterations:**
- **Structure:** The indicator projects five forecast iterations into the future, each spaced by a Fibonacci sequence of bars: 2, 3, 5, 8, and 13 bars ahead. This spacing is inspired by the Fibonacci sequence, which is prevalent in financial market analysis for identifying key levels.
- **Purpose:** Each iteration represents a distinct forecast point where the price may interact with the strata, allowing for a multi-step projection of potential price levels.
3. **Touch Counting:**
- **Definition:** A "touch" occurs when the closing price of a bar is within half the increment of a stratum level.
- **Process:** For each stratum and each forecast iteration, the indicator counts the number of touches within a specified lookback window (e.g., 80 bars), offset by the forecasted position. This ensures that each iteration's touch count is independent and contextually relevant to its forecast horizon.
- **Adjustment:** Each forecast iteration analyzes a unique segment of the lookback window, offset by its forecasted position to ensure independent probability calculations.
4. **Poisson Probability Calculation:**
- **Formula:**
\
\
- **Interpretation:** \(p(k=1)\) represents the probability of exactly one touch occurring within the lookback window for each stratum and iteration.
- **Application:** This probability is used to determine the transparency of each stratum line, where higher probabilities result in more opaque (less transparent) lines, indicating stronger historical significance.
5. **Transparency Mapping:**
- **Calculation:**
\
- **Purpose:** Maps the Poisson probability to a visual transparency level, enhancing the readability of significant strata levels.
- **Outcome:** Strata with higher probabilities (more historical touches) appear more opaque, while those with lower probabilities appear fainter.
---
**📊 **Comparability to Standard Techniques**
1. **Support and Resistance Levels:**
- **Traditional Approach:** Traders identify support and resistance based on historical price reversals, pivot points, or psychological price levels.
- **Poisson Projection:** Automates and quantifies this process by statistically analyzing the frequency of price interactions with specific levels, providing a probabilistic measure of significance.
2. **Statistical Modeling:**
- **Standard Models:** Techniques like Moving Averages, Bollinger Bands, or Fibonacci Retracements offer dynamic and rule-based levels but lack direct probabilistic interpretation.
- **Poisson Projection:** Introduces a discrete event probability framework, offering a unique blend of statistical rigor and visual clarity that complements traditional indicators.
3. **Event-Based Analysis:**
- **Financial Industry Practices:** Event studies and high-frequency trading models often use Poisson processes to model order arrivals or price jumps.
- **Indicator Application:** While not identical, the use of Poisson probabilities in this indicator draws inspiration from event-based modeling, applying it to the context of price level interactions.
---
**💡 **Strengths & Advantages**
1. **Innovative Visualization:**
- Combines statistical probability with traditional support/resistance visualization, offering a fresh perspective on price level significance.
2. **Dynamic Adaptability:**
- Parameters like strata increment, lookback window, and probability threshold are user-defined, allowing customization across different markets and timeframes.
3. **Independent Probability Calculations:**
- Each forecast iteration calculates its own Poisson probability, ensuring that projections are contextually relevant and independent of other iterations.
4. **Clear Visual Cues:**
- Transparency-based coloring intuitively highlights significant price levels, making it easier for traders to identify key areas of interest at a glance.
---
**⚠️ **Limitations & Considerations**
1. **Poisson Assumptions:**
- Assumes that touches occur independently and at a constant average rate (\(\lambda\)), which may not always align with market realities characterized by trends and volatility clustering.
2. **Computational Intensity:**
- Managing multiple iterations and strata can be resource-intensive, potentially affecting performance on lower-powered devices or with very high lookback windows.
3. **Interpretation Complexity:**
- While transparency offers visual clarity, understanding the underlying probability calculations requires a basic grasp of Poisson statistics, which may be a barrier for some traders.
---
**📢 **How to Use It**
1. **Add to TradingView:**
- Open TradingView and navigate to the Pine Script Editor.
- Paste the script above and click **Add to Chart**.
2. **Configure Inputs:**
- **Strata Increment:** Set the desired price step between strata (e.g., `0.1` for 10 cents).
- **Lookback Window:** Define how many past bars to consider for calculating Poisson probabilities (e.g., `80`).
- **Probability Transparency Threshold (%):** Set the threshold percentage to map probabilities to line transparency (e.g., `25%`).
3. **Understand the Forecast Iterations:**
- The indicator projects five forecast points into the future at bar spacings of 2, 3, 5, 8, and 13 bars ahead.
- Each iteration independently calculates its Poisson probability based on the touch counts within its specific lookback window offset by its forecasted position.
4. **Interpret the Visualization:**
- **Opaque Lines:** Indicate higher Poisson probabilities, suggesting historically significant price levels that are more likely to interact again.
- **Fainter Lines:** Represent lower probabilities, indicating less historically significant levels that may be less likely to interact.
- **Forecast Spacing:** The spacing of 2, 3, 5, 8, and 13 bars ahead aligns with Fibonacci principles, offering a natural progression in forecast horizons.
5. **Apply to Trading Strategies:**
- **Support/Resistance Identification:** Use the opaque lines as potential support and resistance levels for placing trades.
- **Entry and Exit Points:** Anticipate price interactions at forecasted levels to plan strategic entries and exits.
- **Risk Management:** Utilize the transparency mapping to determine where to place stop-loss and take-profit orders based on the probability of price interactions.
6. **Customize as Needed:**
- Adjust the **Strata Increment** to fit different price ranges or volatility levels.
- Modify the **Lookback Window** to capture more or fewer historical touches, adapting to different timeframes or market conditions.
- Tweak the **Probability Transparency Threshold** to control the sensitivity of transparency mapping to Poisson probabilities.
**📈 **Practical Applications**
1. **Identifying Key Levels:**
- Quickly visualize which price levels have historically had significant interactions, aiding in the identification of potential support and resistance zones.
2. **Forecasting Price Reactions:**
- Use the forecast iterations to anticipate where price may interact in the near future, assisting in planning entry and exit points.
3. **Risk Management:**
- Determine areas of high probability for price reversals or consolidations, enabling better placement of stop-loss and take-profit orders.
4. **Market Analysis:**
- Assess the strength of market levels over different forecast horizons, providing a multi-layered understanding of market structure.
---
**🔗 **Conclusion**
The *Poisson Projection of Price Levels* bridges the gap between statistical modeling and traditional technical analysis, offering traders a sophisticated tool to quantify and visualize the significance of price levels. By integrating Poisson probabilities with dynamic transparency mapping, this indicator provides a unique and insightful perspective on potential support and resistance zones, enhancing both analysis and trading strategies.
---
**📞 **Contact:**
For support or inquiries, please contact me on TradingView!
---
**📢 **Join the Conversation!**
Have questions, feedback, or suggestions for further enhancements? Feel free to comment below or reach out directly. Your input helps refine and evolve this tool to better serve the trading community.
---
**Happy Trading!** 🚀
Macro ParadoxMacro Paradox: A Detailed Explanation
This indicator utilizes multiple streams of global liquidity data (from the US, China, Japan, the UK, and the Eurozone) and combines them with the DXY and HYG for a “macro plumbing” insight. Surprisingly, this creates a paradoxical predictive relationship: when the green line (Weighted DXY) begins rising, dollar-denominated equities (e.g., SPY) often show bullish momentum about 4–7 days later, and vice versa. Below is an in-depth explanation of why and how this occurs.
Global Liquidity Calculation
The script aggregates the balance sheets or liquidity proxies of major central banks and bond markets, including:
Bank of Japan (multiplied by JPYUSD)
People’s Bank of China (multiplied by CNYUSD)
Bank of England (multiplied by GBPUSD)
US Federal Reserve (WALCL)
European Central Bank (multiplied by EURUSD)
Subtracts reverse repo (RRP) and US Treasury general account (TGA) balances (treas_genac)
This net figure represents the total “flow” of major currency liquidity. Higher net liquidity often indicates rising risk-on appetite; lower liquidity can imply risk-off conditions.
HYG Inclusion for Risk Appetite
HYG (the high-yield corporate bond ETF) is a strong barometer of market risk tolerance. When HYG is robust, it indicates investors are willing to buy higher-yield, lower-rated corporate bonds—implying confidence in economic expansion. The script scales HYG like total liquidity, then applies a user-defined weighting ( hygWeight ) so its movement influences the final combined line.
Scaling and Double-EMA Smoothing
For both liquidity ( total ) and each risk metric (DXY, HYG), the script:
Normalizes them over a lookback window ( lookbackBars ) to a 0–100 scale, aligning different absolute values onto a comparable range.
Applies two EMAs in sequence ( smoothLengthFast , smoothLengthSlow )—similar to a MACD-style smoothing—to remove noise and reveal underlying trend momentum more clearly.
By smoothing twice, you get a cleaner signal, making it easier to spot turning points without the usual whipsaws seen with single-smoothing.
Weighted by the Chart’s Price Action
To reflect how these macro flows interact with the specific ticker, the script compares close price to its EMA ( myTickerEma ). The ratio ( close / myTickerEma ) is raised to weightPower , amplifying how overextended or under-extended the ticker is relative to its own trend. The final scaled lines are multiplied by this “ weightFactor ,” adapting them to each ticker’s current price trend.
“Paradoxical” DXY Relationship Explained
Conventionally, a strengthening US dollar can pressure risk assets. However, this script shows a rising Weighted DXY line (green) is often followed by bullishness in dollar-based equities (e.g., SPY) several days later. Why?
When global liquidity is high, capital can flow into US assets, supporting both the dollar and equities.
HYG being strong signals credit-fueled demand; combined with global liquidity, this can push bond and equity prices higher simultaneously.
As the DXY “catches a bid,” it hints at global investors allocating to US assets. This often takes 4–7 days to reflect in the broader equity market, giving the illusion of a “paradox.”
Practical Usage and Timeframes
Because major liquidity data (from central banks, RRP, TGA, etc.) is updated once a day or weekly, smaller intraday charts (like 1-hour) will not accurately capture these macro flows. For this reason, the indicator is most reliable on Daily charts. At higher frequency, signals can be misleading because the macro data does not refresh that often.
Why It’s Unique
Combines total global net liquidity and credit risk sentiment (HYG) into one line, then cross-compares it to DXY for insight into capital flows.
Applies a two-stage EMA smoothing for each series, reducing noise and clarifying the macro trend signal.
Weights the signal by the chart’s own price trend, adapting to each ticker’s technical conditions.
Reveals an unusual yet historically consistent “delayed bullishness” effect when the Weighted DXY (green) starts climbing.
A rising Weighted DXY line (green) often foretells— 4 to 7 days later —an upswing in US equities, contrary to the typical notion that a stronger dollar always harms risk assets. By blending net global liquidity, HYG’s risk appetite measure, and a weighting factor keyed to the chart’s trend, this indicator provides a novel, smoother view of macro flows.
Note: For best results, use Daily or higher timeframes to align with the release schedule of the underlying liquidity data. This avoids short-term noise that doesn’t reflect actual macro changes.
Indicador CME - DOLAR BRLConversão do Dólar em Real pelo CME. Normalmente o gráfico do CME é Dólar/Real. Com esse indicador é possível inverter e obter o valor do real em dólar.
Mupf Wick - Extended Valid Lines
This indicator identifies and tracks wick-based price entry strategies on higher timeframes. It is designed for traders who utilize wick-driven logic for identifying significant price levels.
How to Use
Select Timeframe:
Set the higher timeframe for wick detection in the settings (default is 4-hour).
Customize Tolerance and Visuals:
Adjust the wick tolerance percentage and enable/disable visualization options based on your trading strategy.
Analyze Lines:
Green lines indicate validated bullish wicks (support).
Red lines indicate validated bearish wicks (resistance).
Blue or purple lines show invalidated levels due to double wicks or body overlaps.
Use as Confluence:
Combine this indicator with your broader strategy to identify high-probability zones for entries or exits.
Previous wicks:
Double wicks:
Double body's:
Features
Wick Detection Across Different Timeframes
Tracks wicks on a user-defined higher timeframe (default: 4-hour) to highlight potential support and resistance levels.
Dynamic Valid Line Classification
Valid Lines: Lines validated when the price crosses the body of subsequent candles.
Invalid Lines: Lines invalidated by overlapping wick conditions.
Double Wick/Body Detection: Highlights invalid lines due to double wicks or body overlaps.
Customizable Visualization
Configurable line width and colors for valid, invalid, and other conditions.
Optional visibility for expired wicks, double wicks, and invalid body overlaps.
Tolerance-Based Wick Filtering
Includes a user-adjustable tolerance percentage to define how closely a wick must align with price to trigger validation or invalidation.
Known Issues
Timeframe Dependency:
The indicator only works correctly on the specified candle timeframe (default: 4-hour). Using it on other timeframes without adjustment may cause errors or misaligned lines.
Memory Limitations:
Due to Pine Script's memory constraints, some previous wicks or invalid wicks may be missed if too many lines / options are tracked simultaneously.
Missing Alerts for Entry Triggers:
The indicator currently lacks built-in alerts for entry triggers based on line validation/invalidation events. This must be monitored manually.
Future Enhancements
Support for multi-timeframe compatibility.
Improved memory handling to track more historical wicks.
Addition of alert functionality for real-time trade signals.
This tool is ideal for traders focusing on price action and wick-based strategies, providing visual clarity on important market levels.
Santa Clause RallyA Santa Claus rally is a calendar effect that involves a rise in stock prices during the last 5 trading days in December and the first 2 trading days in the following January.
The Santa Claus rally can potentially predict the future trend of stocks in the coming year.
Merry Christmas and Happy New Year 🎄🎄🎄
PowerStrike Pro V3Purpose of the Script
"PowerStrike Pro V3" is a custom indicator designed to generate high-accuracy buy/sell signals by combining multiple technical analysis tools. This script is optimized for trend-following, scalping, and support/resistance strategies. It integrates popular indicators such as RSI, Supertrend, Bollinger Bands, and dynamic support/resistance levels to provide traders with reliable signals.
Components of the Script and How It Works
The script combines the following key components, each contributing to the total signal strength based on user-defined weights. Below is a detailed explanation of how each component works and how it contributes to the overall score:
1. RSI (Relative Strength Index)
How It Works:
RSI identifies overbought (above 70) and oversold (below 30) conditions in the market.
The script uses RSI values to measure the strength of the trend and generate buy/sell signals.
When RSI is in the oversold zone, it strengthens buy signals. When in the overbought zone, it strengthens sell signals.
Contribution to Total Score:
RSI's contribution is calculated based on its strength in the oversold or overbought zones.
The final contribution is weighted by the user-defined "RSI Weight" and added to the total score.
2. Support and Resistance Levels
How It Works:
The script dynamically calculates recent peaks (resistance) and valleys (support) using a user-defined lookback period.
These levels are plotted on the chart as dynamic support and resistance lines.
The proximity of the price to these levels strengthens the signals.
Contribution to Total Score:
If the price is near a support level, it increases the strength of buy signals.
If the price is near a resistance level, it increases the strength of sell signals.
The contribution is weighted by the "Support/Resistance Weight" and added to the total score.
3. Supertrend Indicator
How It Works:
Supertrend uses ATR (Average True Range) and a multiplier to determine the trend direction.
The script uses Supertrend's direction changes as a filter for buy/sell signals.
When Supertrend is in an uptrend, it strengthens buy signals. When in a downtrend, it strengthens sell signals.
Contribution to Total Score:
Supertrend's contribution is weighted by the "Supertrend Weight" and added to the total score.
4. Bollinger Bands
How It Works:
Bollinger Bands measure price volatility and identify potential support/resistance levels.
The script generates buy signals when the price crosses above the lower band and sell signals when it crosses below the upper band.
Contribution to Total Score:
A crossover above the lower band increases the strength of buy signals.
A crossover below the upper band increases the strength of sell signals.
The contribution is weighted by the "Bollinger Bands Weight" and added to the total score.
5. Order Book Data
How It Works:
The script analyzes bid/ask volumes from the order book to assess market depth.
High bid volume near support levels strengthens buy signals.
High ask volume near resistance levels strengthens sell signals.
Contribution to Total Score:
Order book data is weighted by the "Order Book Weight" and added to the total score.
Signal Types and Their Meaning
The script generates two types of signals:
Weak Signals:
Weak signals indicate the early stages of a trend or minor corrections.
These are represented by small green (buy) or red (sell) triangles on the chart.
Weak signals are suitable for low-risk trades or scalping strategies.
Strong Signals:
Strong signals indicate the continuation of a trend or significant reversal points.
These are represented by larger green (buy) or red (sell) arrows on the chart.
Strong signals are suitable for higher-risk, higher-reward trades.
Total Score Calculation
The script calculates the total buy and sell scores by combining the weighted contributions of all components. The formula for the total score is as follows:
Copy
Total Buy Score = (RSI Buy Strength * RSI Weight) + (Support Strength * Support/Resistance Weight) + (Supertrend Buy Strength * Supertrend Weight) + (Bollinger Buy Strength * Bollinger Weight) + (Order Book Buy Strength * Order Book Weight)
Total Sell Score = (RSI Sell Strength * RSI Weight) + (Resistance Strength * Support/Resistance Weight) + (Supertrend Sell Strength * Supertrend Weight) + (Bollinger Sell Strength * Bollinger Weight) + (Order Book Sell Strength * Order Book Weight)
The total score is then compared to user-defined thresholds to generate weak or strong signals. For example:
A total buy score above 80% generates a weak buy signal.
A total buy score above 85% generates a strong buy signal.
Recommended Strategies
Trend Following: Use strong signals to trade in the direction of the main trend.
Scalping: Use weak signals to capture short-term price movements.
Support/Resistance Trading: Use the dynamically plotted support and resistance levels to identify reversal points.
How to Use the Script
Weight Settings:
Adjust the weights for each component (RSI, Supertrend, Bollinger Bands, etc.) in the script settings to customize the signal strength calculation.
Signal Thresholds:
Set the thresholds for weak and strong signals (e.g., 80% for weak signals, 85% for strong signals).
Chart Visualization:
The script automatically plots buy/sell signals on the chart. Use these signals in conjunction with your trading strategy.
Unique Features of the Script
Dynamic Weighting: Each component's contribution to the total score can be customized using user-defined weights.
Integrated Support/Resistance: The script dynamically calculates and plots support/resistance levels, enhancing signal accuracy.
Order Book Analysis: The inclusion of order book data provides additional confirmation for signals.
Final Notes
While "PowerStrike Pro V3" combines multiple indicators to generate reliable signals, no indicator guarantees 100% accuracy. Always use proper risk management and combine this script with other analysis tools for the best results
Phase Cross Strategy with Zone### Introduction to the Strategy
Welcome to the **Phase Cross Strategy with Zone and EMA Analysis**. This strategy is designed to help traders identify potential buy and sell opportunities based on the crossover of smoothed oscillators (referred to as "phases") and exponential moving averages (EMAs). By combining these two methods, the strategy offers a versatile tool for both trend-following and short-term trading setups.
### Key Features
1. **Phase Cross Signals**:
- The strategy uses two smoothed oscillators:
- **Leading Phase**: A simple moving average (SMA) with an upward offset.
- **Lagging Phase**: An exponential moving average (EMA) with a downward offset.
- Buy and sell signals are generated when these phases cross over or under each other, visually represented on the chart with green (buy) and red (sell) labels.
2. **Phase Zone Visualization**:
- The area between the two phases is filled with a green or red zone, indicating bullish or bearish conditions:
- Green zone: Leading phase is above the lagging phase (potential uptrend).
- Red zone: Leading phase is below the lagging phase (potential downtrend).
3. **EMA Analysis**:
- Includes five commonly used EMAs (13, 26, 50, 100, and 200) for additional trend analysis.
- Crossovers of the EMA 13 and EMA 26 act as secondary buy/sell signals to confirm or enhance the phase-based signals.
4. **Customizable Parameters**:
- You can adjust the smoothing length, source (price data), and offset to fine-tune the strategy for your preferred trading style.
### What to Pay Attention To
1. **Phases and Zones**:
- Use the green/red phase zone as an overall trend guide.
- Avoid taking trades when the phases are too close or choppy, as it may indicate a ranging market.
2. **EMA Trends**:
- Align your trades with the longer-term trend shown by the EMAs. For example:
- In an uptrend (price above EMA 50 or EMA 200), prioritize buy signals.
- In a downtrend (price below EMA 50 or EMA 200), prioritize sell signals.
3. **Signal Confirmation**:
- Consider combining phase cross signals with EMA crossovers for higher-confidence trades.
- Look for confluence between the phase signals and EMA trends.
4. **Risk Management**:
- Always set stop-loss and take-profit levels to manage risk.
- Use the phase and EMA zones to estimate potential support/resistance areas for exits.
5. **Whipsaws and False Signals**:
- Be cautious in low-volatility or sideways markets, as the strategy may generate false signals.
- Use additional indicators or filters to avoid entering trades during unclear market conditions.
### How to Use
1. Add the strategy to your chart in TradingView.
2. Adjust the input settings (e.g., smoothing length, offsets) to suit your trading preferences.
3. Enable the strategy tester to evaluate its performance on historical data.
4. Combine the signals with your own analysis and risk management plan for best results.
This strategy is a versatile tool, but like any trading method, it requires proper understanding and discretion. Always backtest thoroughly and trade with discipline. Let me know if you need further assistance or adjustments to the strategy!
Fibonacci Trading Strategy (Auto Levels)How It Works
Swing Highs and Lows Detection:
The script identifies the highest high and lowest low over a specified lookback period (default: 50 candles). These points are used as the basis for Fibonacci calculations.
Fibonacci Levels:
Fibonacci retracement levels: 0%, 38.2%, 50%, 61.8%, 78.6%, and 100%.
Fibonacci extension levels: 127.2%, 161.8%, 200%, 261.8%, and 361.8%.
Each level is plotted on the chart with a specific color and labeled with the corresponding price.
Entry Zones:
Pullback Area: Between the 50% and 61.8% retracement levels. This area is highlighted in green, indicating a potential entry for conservative traders.
Full Margin Area: Between the 61.8% and 78.6% retracement levels. This area is highlighted in red, suggesting a higher-risk entry for aggressive traders.
Stop Loss (SL):
The Stop Loss is placed at the 78.6% Fibonacci retracement level. A dotted red line is drawn at this level to provide a visual reference for risk management.
Entry labels include the Stop Loss price for clarity.
Take Profit (TP) Levels:
Multiple take-profit targets are identified using Fibonacci extension levels (127.2%, 161.8%, 200%, 261.8%, and 361.8%).
Each level is labeled with the price and target percentage.
Visual Aids:
The script dynamically labels each Fibonacci level with its corresponding price.
Entry points (Pullback and Full Margin) are marked with clear labels, including the recommended Stop Loss.
Background highlights help distinguish the Pullback and Full Margin areas.
Strategy Highlights
Risk Management:
Incorporates a well-defined Stop Loss at the 78.6% level to limit downside risk.
Multiple take-profit levels help traders scale out of positions gradually.
Automation:
Automatically recalculates levels when new swing highs or lows are detected, ensuring accuracy in dynamic markets.
Customizability:
Users can adjust the lookback period to suit different timeframes or trading styles.
Clarity:
Clean visuals and detailed labels ensure the strategy is easy to interpret and apply.
When to Use
The strategy is suitable for trend-following traders looking to enter during pullbacks in an established trend.
It works best in trending markets where Fibonacci levels often act as strong support or resistance.
Example Scenario
Bullish Setup:
Price retraces to the 50%-61.8% area (Pullback Area) after a swing high.
A buy order is placed in this zone, with the Stop Loss at the 78.6% level.
Profit targets are set at the 127.2%, 161.8%, and higher Fibonacci extensions.
Bearish Setup:
In a downtrend, price retraces upward to the 50%-61.8% zone.
A sell order is placed, with the Stop Loss at the 78.6% level and take-profit levels below.
PreMarket_Estimator Portfolio [n_dot]AMEX:SOXL ; NASDAQ:TQQQ ; AMEX:FNGU ; AMEX:SOXS ; NASDAQ:SQQQ ; AMEX:FNGD
Strategy Core Idea:
I focus on stocks that are expected to show significant price movements (gaps) during the premarket, usually due to news or earnings reports. I record the highest price formed during the premarket, and if the price exceeds this level after the market opens, I go LONG. Based on my experience, it’s advisable to exit after a few percentage points of increase, as the premarket boom often corrects itself.
Usage:
The indicator is best used in pairs: Pre_Market_Estimator Single and Pre_Market_Estimator Portfolio.
In this portfolio version, you can set up 6 different instruments, which are displayed stacked vertically on the screen, while the single version monitors only one instrument. The portfolio does not plot charts at the actual price levels but offsets them vertically, displaying the current prices in a label at the end of each chart.
Settings:
Time point 1: Start of the observation period.
Time point 2: End of the observation period / Start of the trading period.
GAP: is used to adjust the distance between the charts displayed in the portfolio view. This allows you to customize the spacing for better readability and visualization of the monitored instruments.
Usage:
Set the timeframe period to "1m".
Set Time point 1 to the start of the premarket session on the current day (e.g., NYSE: 9:00).
Set Time point 2 to the market open (e.g., NYSE: 9:30).
The indicator monitors the highest price during the premarket period, marking it with a blue line.
During the subsequent trading period, if the price exceeds the premarket high, it generates a buy signal marked with a blue plus sign.
Limitations:
The premarket prediction typically provides actionable signals during the first 30 minutes to 1 hour of the trading session. After this, the trend is usually driven by daily market events or news.
To reduce data usage, the portfolio version of the indicator (which monitors 6 instruments simultaneously) only loads the last 24 hours of data (60 * 24 minutes). After this, the chart stops providing signals, and the time points need to be reset.
Additional Use Cases:
This type of breakout monitoring is not only suitable for observing premarket events but can also provide relevant information before major announcements.
For example, in the case of central bank rate hikes:
Set Point 1 to 1 hour before the announcement.
Set Point 2 to the time of the announcement.
I hope this contributes to your success!
Stock Scanner - 38 AssetsPullback Scanner and Trading Strategy:
The Scanner's Purpose:
This tool helps identify stocks and futures from a set-list that are in a strong uptrend (above 200 SMA) but experiencing a temporary pullback (RSI below 38), creating potential buying opportunities.
Load 38 Favourite Stocks. They need to be bullish ie: Trading usually above 200 SMA. A drop down switch lets you choose which group. You can find suitable stocks using the filter at FINVIZ:
use on 4hr Timeframes and Above
You must use this on at least the 4hr timeframe, otherwise the 200SMA is not truly placed correctly and a valid trade depends upon the price action being ABOVE the 200SMA.
finviz.com
Key Components:
200 Simple Moving Average (SMA)
Acts as a trend filter
Price above 200 SMA indicates a long-term uptrend
Helps avoid trading against the main trend
Relative Strength Index (RSI)
Set to 38 as the oversold threshold
Identifies temporary weakness in strong trends
Acts as the pullback confirmation. You could add an RSI indicator to the chart for monitoring.
Visual Signals:
Green row: Indicates both conditions are met (price > 200 SMA and RSI < 38)
Yellow triangle: Appears at price bottom when RSI drops below 38
Yellow 200 SMA line: Shows the trend direction and potential support
Trade Setup:
First Requirement: Price must be trading above the 200 SMA
Second Requirement: Wait for RSI to drop below 38
Entry Trigger: When both conditions align (row turns green)
Risk Management: Set stop loss below recent swing low
Exit: When RSI moves above 53 or price crosses below 200 SMA
The scanner monitors multiple instruments simultaneously, allowing traders to identify setups across different markets without manually checking each chart. When a row turns green, that instrument deserves closer attention for potential trade setup.
Example Trade:
Looking at the chart of Apple (AAPL), the yellow triangles show where RSI dropped below 38 while price remained above the rising 200 SMA, providing multiple long entry opportunities in an established uptrend. Actually Apple may be better with RSI below 26.
If you use ctrader, I have made a cbot version of this to automatically take trades on the ctrader platform: eg: XAUUSD i.postimg.cc
Detecting Sideways Market or Strong Trends| Copy Trade Tungdubai**Tool Description**:
The **"Detecting Sideways Market or Strong Trends | Copy Trade Tungdubai"** tool is designed to help traders identify two key market conditions:
1. **Sideways Market**:
- This condition is detected when the ADX is below 20, the price stays within the Bollinger Bands, and the RSI is between 45 and 55.
- When the market is sideways, the chart background will turn yellow as a visual alert.
2. **Strong Trend Market**:
- This condition is identified when the ADX is above 25, and either the price breaks out of the Bollinger Bands or the RSI surpasses the overbought (70) or oversold (30) levels.
- When the market is in a strong trend, the chart background will turn blue as a visual alert.
**Key Components of the Tool**:
- **ADX**: Measures the strength of the market trend, with key thresholds at 20 and 25.
- **Bollinger Bands**: Helps determine volatility and checks if the price is within or outside the bands.
- **RSI**: Measures momentum, helping identify overbought and oversold levels.
**Visual Features on the Chart**:
- ADX, RSI, and Bollinger Bands are clearly plotted with their respective key thresholds for easier recognition of market conditions.
- The chart background changes color to reflect the current market condition (yellow for sideways, blue for strong trends).
**Alerts**:
- Alerts are triggered when the market enters either a sideways or strong trend phase, providing notifications to help users act promptly.
This tool serves as a practical aid in recognizing market conditions, allowing traders to make informed decisions aligned with their strategies.
**Mô tả công cụ**:
Công cụ **"Detecting Sideways Market or Strong Trends | Copy Trade Tungdubai"** được thiết kế để giúp các nhà giao dịch xác định hai trạng thái chính của thị trường:
1. **Thị trường đi ngang (Sideways)**:
- Điều kiện được xác định dựa trên chỉ số ADX thấp hơn ngưỡng 20, giá nằm trong dải Bollinger Bands, và chỉ số RSI dao động trong khoảng từ 45 đến 55.
- Khi thị trường đi ngang, nền của biểu đồ sẽ chuyển sang màu vàng để cảnh báo trực quan.
2. **Thị trường bùng nổ sóng mạnh (Strong Trend)**:
- Điều kiện được xác định khi ADX vượt qua ngưỡng 25 và giá phá vỡ dải Bollinger Bands (hoặc) chỉ số RSI vượt ngưỡng quá mua 70 hoặc quá bán 30.
- Khi thị trường bùng nổ sóng mạnh, nền biểu đồ sẽ chuyển sang màu xanh để cảnh báo trực quan.
**Các thành phần chính của công cụ**:
- **ADX**: Được sử dụng để đo sức mạnh xu hướng thị trường, với các ngưỡng quan trọng là 20 và 25.
- **Bollinger Bands**: Được sử dụng để xác định mức độ biến động và kiểm tra giá nằm trong hay ngoài dải.
- **RSI**: Dùng để đo mức độ quá mua/quá bán, xác định động lượng giá.
**Hiển thị trên biểu đồ**:
- Các đường ADX, RSI, và Bollinger Bands được vẽ rõ ràng, cùng với các ngưỡng quan trọng (hỗ trợ nhận biết trạng thái thị trường).
- Nền biểu đồ thay đổi màu sắc tương ứng với điều kiện thị trường.
**Cảnh báo**:
- Cảnh báo sẽ được kích hoạt khi thị trường rơi vào trạng thái đi ngang hoặc bùng nổ sóng mạnh, với các thông báo giúp người dùng hành động kịp thời.
Công cụ này là một trợ thủ hữu ích trong việc nhận biết trạng thái thị trường, từ đó giúp các nhà giao dịch đưa ra quyết định phù hợp với chiến lược của mình.
Dynamic Market ScannerDynamic Market Scanner is a powerful tool for analyzing financial markets, combining a variety of indicators to provide clear and understandable signals.
Key Features:
- Signal Generation:
The main signals "Buy", "Sell", and "Hold" are formed based on the analysis of indicators:
- MACD
- RSI
- SMA
- EMA
- WMA
- Hull MA
Additional Analytical Tools:
- ATR is used to assess volatility and helps to understand the risk of the current market situation.
- SMA Ichimoku does not generate signals but is used to assess their accuracy.
- If the price is above the SMA, "Buy" signals are more likely, as this confirms the strength of the upward movement.
- If the price is below the SMA, "Buy" signals require additional confirmations.
Dashboard:
Displays the current price position relative to the indicators, helping the trader understand how strong or weak the current signals are.
Advantages of Using:
1. Signal Filtering:
The price position relative to the SMA Ichimoku helps to assess the likelihood of successful trades.
2. Volatility Analysis:
ATR provides additional information about risks and market fluctuations.
3. Comprehensive Approach:
Signal generation is based on a combination of key indicators, offering a multifaceted view of the market.
Explanation of Percent Calculation in the Table:
- The table shows the values of indicators such as MACD, ATR, EMA, SMA, WMA, and Hull MA in percentages. Percentages are calculated based on the current value of the indicator relative to its maximum and minimum.
- Percentages are displayed for each indicator, allowing traders to assess market conditions based on their current values.
Dynamic Market Scanner will become a reliable assistant in your technical analysis toolkit, providing a comprehensive overview of market conditions and helping to make informed trading decisions.
MW:TA Days of the WeekENG: Vertical separators to easily detect days of the week and see which past liquidity was taken down. Screenshot example contains days of the week indicator and manually drawn lines of grabbed liquidity. Useful for trades based on liquidity grab and reaction.
Tested on Forex, Crypto, Indexes, Stocks, Commodities markets.
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РУС: Вертикальные разделители для визуального определения дней недели и просмотра снятой ликвидности на графике. На скриншоте отмечен индикатор разделительных периодов (дней) и вручную нарисованные линии, которые отмечают снятую ликвидность и реакцию цены на снятие. Полезно для тех трейдеров, которые торгуют по реакции на снятую ликвидность.
Протестировано на рынках Форекс, Крипто, ИНдексов, Акций и Сырья.
FuTech : MACD Crossovers Advanced Alert Lines=============================================================
Indicator : FuTech: MACD Crossovers Advanced Alert Lines
Overview:
The "FuTech: MACD Crossovers Advanced Alert Lines" indicator is designed to assist traders in identifying key technical patterns using the :-
1. MACD (Moving Average Convergence Divergence) and
2. Golden/Death Crossovers
By visualizing these indicators directly on the chart with advanced lines, it helps traders make more informed decisions on when to enter or exit trades.
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Key Features of "FuTech: MACD Crossovers Advanced Alert Lines":
1. MACD Crossovers:
a) The MACD is one of the most widely used indicators for identifying momentum shifts and potential buy/sell signals. This indicator plots vertical lines on the chart whenever the MACD line crosses the signal line.
b) Upward Crossover (Bullish Signal) : When the MACD line crosses above the signal line, a green vertical line will appear, indicating a potential buying opportunity.
c) Downward Crossover (Bearish Signal) : When the MACD line crosses below the signal line, a red vertical line will appear, signaling a potential selling opportunity.
2. Golden Cross & Death Cross:
a) The Golden Cross occurs when the price moves above a long-term moving average (like the 50-day moving average), signaling a potential upward trend.
b) The Death Cross occurs when the price moves below a long-term moving average, signaling a potential downward trend.
c) These crossovers are displayed with customizable lines on the chart to easily spot when the market is shifting direction.
d) Golden Cross (Bullish Signal) : A blue vertical line appears when the price crosses above the selected long-term moving average.
e) Death Cross (Bearish Signal) : A purple vertical line appears when the price crosses below the selected long-term moving average.
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Customization Options:
This indicator offers several customization options to suit your trading preferences:
1) MACD Settings:
a) Choose between different moving average types (EMA, SMA, or VWMA) for calculating the MACD.
b) Adjust the lengths of the fast, slow, and signal MACD periods.
c) Control the width and color of the vertical lines drawn on the chart for both up and down crossovers.
2) Golden Cross / Death Cross Settings:
a) Select the moving average type for the Golden Cross / Death Cross (EMA, SMA, or VWMA).
b) Define the lookback period for calculating the Golden Cross / Death Cross.
c) Customize the appearance of the Golden and Death Cross lines, including their width and color.
You can use both as well as either of the MACD lines or Golden Crossover / Death Crossover Lines respectively as per your trading strategies
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How "FuTech: MACD Crossovers Advanced Alert Lines" indicator Works:
a) The indicator monitors the price and calculates the MACD and Golden/Death Crosses.
b) When the MACD line crosses above or below the signal line, or when the price crosses above or below the long-term moving average, it plots a vertical line on the chart.
c) These lines help traders quickly spot potential turning points in the market, providing clear signals to act upon.
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Use Case:
a) Swing Traders: The indicator is useful for spotting momentum shifts and trend reversals, helping you time entries and exits for short- to medium-term trades.
b) Long-Term Traders: The Golden and Death Cross signals help identify major trend changes, giving insights into potential market shifts.
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Why Use This "FuTech: MACD Crossovers Advanced Alert Lines" Indicator ?
a) Clear Visuals : The vertical lines provide clear and easy-to-spot signals for MACD crossovers and Golden/Death Crosses.
b) Customizable : Adjust settings for your personal trading strategy, whether you're focusing on short-term momentum or long-term trend shifts.
c) Supports Decision Making : With its advanced line plotting and customizable features, this indicator helps you make quicker and more informed trading decisions.
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How to Use:
a) MACD Crossovers: Look for green lines to signal potential buying opportunities (when the MACD line crosses above the signal line) and red lines for selling opportunities (when the MACD line crosses below the signal line).
b) Golden Cross / Death Cross: Use the blue lines to confirm when a positive trend may begin (Golden Cross) and purple lines to warn when a negative trend may start (Death Cross).
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Conclusion:
"FuTech: MACD Crossovers Advanced Alert Lines" indicator combines two powerful technical analysis tools, the MACD and Golden/Death Crosses, to provide clear, actionable signals on your chart.
By customizing the appearance of these signals and combining them with your trading strategy, you can enhance your decision-making process and improve your trading outcomes.
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Thank you !
Jai Swaminarayan Dasna Das !
He Hari ! Bas Ek Tu Raji Tha !
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Rolling Window Geometric Brownian Motion Projections📊 Rolling GBM Projections + EV & Adjustable Confidence Bands
Overview
The Rolling GBM Projections + EV & Adjustable Confidence Bands indicator provides traders with a robust, dynamic tool to model and project future price movements using Geometric Brownian Motion (GBM). By combining GBM-based simulations, expected value (EV) calculations, and customizable confidence bands, this indicator offers valuable insights for decision-making and risk management.
Key Features
Rolling GBM Projections: Simulate potential future price paths based on drift (μμ) and volatility (σσ).
Expected Value (EV) Line: Represents the average projection of simulated price paths.
Confidence Bands: Define ranges where the price is expected to remain, adjustable from 51% to 99%.
Simulation Lines: Visualize individual GBM paths for detailed analysis.
EV of EV Line: A smoothed trend of the EV, offering additional clarity on price dynamics.
Customizable Lookback Periods: Adjust the rolling lookback periods for drift and volatility calculations.
Mathematical Foundation
1. Geometric Brownian Motion (GBM)
GBM is a mathematical model used to simulate the random movement of asset prices, described by the following stochastic differential equation:
dSt=μStdt+σStdWt
dSt=μStdt+σStdWt
Where:
StSt: Price at time tt
μμ: Drift term (expected return)
σσ: Volatility (standard deviation of returns)
dWtdWt: Wiener process (standard Brownian motion)
2. Drift (μμ) and Volatility (σσ)
Drift (μμ): Represents the average logarithmic return of the asset. Calculated using a simple moving average (SMA) over a rolling lookback period.
μ=SMA(ln(St/St−1),Lookback Drift)
μ=SMA(ln(St/St−1),Lookback Drift)
Volatility (σσ): Measures the standard deviation of logarithmic returns over a rolling lookback period.
σ=STD(ln(St/St−1),Lookback Volatility)
σ=STD(ln(St/St−1),Lookback Volatility)
3. Price Simulation Using GBM
The GBM formula for simulating future prices is:
St+Δt=St×e(μ−12σ2)Δt+σϵΔt
St+Δt=St×e(μ−21σ2)Δt+σϵΔt
Where:
ϵϵ: Random variable from a standard normal distribution (N(0,1)N(0,1)).
4. Confidence Bands
Confidence bands are determined using the Z-score corresponding to a user-defined confidence percentage (CC):
Upper Band=EV+Z⋅σ
Upper Band=EV+Z⋅σ
Lower Band=EV−Z⋅σ
Lower Band=EV−Z⋅σ
The Z-score is computed using an inverse normal distribution function, approximating the relationship between confidence and standard deviations.
Methodology
Rolling Drift and Volatility:
Drift and volatility are calculated using logarithmic returns over user-defined rolling lookback periods (default: μ=20μ=20, σ=16σ=16).
Drift defines the overall directional tendency, while volatility determines the randomness and variability of price movements.
Simulations:
Multiple GBM paths (default: 30) are generated for a specified number of projection candles (default: 12).
Each path is influenced by the current drift and volatility, incorporating random shocks to simulate real-world price dynamics.
Expected Value (EV):
The EV is calculated as the average of all simulated paths for each projection step, offering a statistical mean of potential price outcomes.
Confidence Bands:
The upper and lower bounds of the confidence bands are derived using the Z-score corresponding to the selected confidence percentage (e.g., 68%, 95%).
EV of EV:
A running average of the EV values, providing a smoothed perspective of price trends over the projection horizon.
Indicator Functionality
User Inputs:
Drift Lookback (Bars): Define the number of bars for rolling drift calculation (default: 20).
Volatility Lookback (Bars): Define the number of bars for rolling volatility calculation (default: 16).
Projection Candles (Bars): Set the number of bars to project future prices (default: 12).
Number of Simulations: Specify the number of GBM paths to simulate (default: 30).
Confidence Percentage: Input the desired confidence level for bands (default: 68%, adjustable from 51% to 99%).
Visualization Components:
Simulation Lines (Blue): Display individual GBM paths to visualize potential price scenarios.
Expected Value (EV) Line (Orange): Highlight the mean projection of all simulated paths.
Confidence Bands (Green & Red): Show the upper and lower confidence limits.
EV of EV Line (Orange Dashed): Provide a smoothed trendline of the EV values.
Current Price (White): Overlay the real-time price for context.
Display Toggles:
Enable or disable components (e.g., simulation lines, EV line, confidence bands) based on preference.
Practical Applications
Risk Management:
Utilize confidence bands to set stop-loss levels and manage trade risk effectively.
Use narrower confidence intervals (e.g., 50%) for aggressive strategies or wider intervals (e.g., 95%) for conservative approaches.
Trend Analysis:
Observe the EV and EV of EV lines to identify overarching trends and potential reversals.
Scenario Planning:
Analyze simulation lines to explore potential outcomes under varying market conditions.
Statistical Insights:
Leverage confidence bands to understand the statistical likelihood of price movements.
How to Use
Add the Indicator:
Copy the script into the TradingView Pine Editor, save it, and apply it to your chart.
Customize Settings:
Adjust the lookback periods for drift and volatility.
Define the number of projection candles and simulations.
Set the confidence percentage to tailor the bands to your strategy.
Interpret the Visualization:
Use the EV and confidence bands to guide trade entry, exit, and position sizing decisions.
Combine with other indicators for a holistic trading strategy.
Disclaimer
This indicator is a mathematical and statistical tool. It does not guarantee future performance.
Use it in conjunction with other forms of analysis and always trade responsibly.
Happy Trading! 🚀
MA Resist TrendThis Pine Script™ code designed to provide insights into price trends and potential buy/sell signals based on a moving average of resistance levels. It features dynamic calculations of a resistance line and a base moving average, enabling traders to visualize trend direction and reversal points effectively.
Key Features:
1. Moving Average Selection:
The indicator supports a wide variety of moving averages, including:
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
HMA (Hull Moving Average)
McGinley Dynamic
RMA (Relative Moving Average)
MD (Mode Average)
WMA (Weighted Moving Average)
VWMA (Volume-Weighted Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
This provides flexibility in tailoring the indicator to suit different market conditions and trading styles.
2. Dynamic Resistance Calculation:
MAR: A smoothed moving average of the mid-range between highest price period and lowest price period. This represents the main trend resistance line.
3. Base Line and Resistance Line:
The base line is calculated as the EMA of the closing price.
The resistance line is derived by subtracting the distance between MAR and the base line from the base line. This distance is used to identify potential reversal points.
4. Color Coding:
The MAR line changes color based on its relationship with the current closing price:
Green (lime): Indicates bullish conditions (price above mar).
Red: Indicates bearish conditions (price below mar).
5. Buy and Sell Signals:
A buy signal is triggered when the MAR line crosses below the resistance line.
A sell signal is triggered when the MAR line crosses above the resistance line.
Signals are displayed using labeled shapes on the chart:
"BUY" shape appears below the bar for buy signals.
"SELL" shape appears above the bar for sell signals.
6. Customizable Parameters:
len: Length of the moving average (default: 14).
ma: Type of moving average to use.
lb: Lookback period for high and low prices (default: 3).
smt: Smoothing factor for the mar line (default: 3).
Visualization:
The indicator plots the following on the price chart:
MAR Line: Represents the dynamic resistance line, colored based on market conditions.
Resistance Line: A yellow line indicating the calculated resistance levels.
Buy/Sell Labels: Visual markers indicating potential trade opportunities.
Use Cases:
Trend Identification:
The MAR line provides insights into the current trend direction.
Color changes highlight transitions between bullish and bearish conditions.
Reversal Detection:
Buy and sell signals help identify potential trend reversals.
Dynamic Resistance Levels:
The resistance line offers additional context for understanding price action and possible resistance points.
Notes:
This indicator is particularly useful for trend-following traders who incorporate moving averages into their strategies.
It supports a wide range of moving averages, making it versatile across different asset classes and timeframes.
Traders can experiment with different len, lb, and smt values to fine-tune the indicator's responsiveness.
This script is provided for prediction purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Market Cap LevelsThis indicator zeroes in on those key “round number” market caps and marks them right on your price chart, converting cumbersome billions into crisp, easy-to-track figures (e.g., “10 B”). Instead of getting lost in massive numbers, you’ll instantly see whether a stock is flirting with a big valuation threshold.
Why It Matters & How Big Players Might Use It:
Round-Number Magnet: Institutions often treat nice, round market caps as psychological checkpoints. When a company edges near or beyond SEED_TVCODER77_ETHBTCDATA:5B , SEED_TVCODER77_ETHBTCDATA:10B , or even $500B, it can spark new waves of interest—or caution.
Behavioral Insights: These lines can act like magnets or barriers, hinting at spots where price action could shift if the broader market starts perceiving the company as hitting “the next major level.”
Clean Visuals, Quick Decisions: By placing these key valuations directly on your chart, you can instantly gauge whether a stock is hovering just below or sailing above a major capital milestone—no calculator needed.
IU Higher Timeframe MA Cross StrategyIU Higher Timeframe MA Cross Strategy
The IU Higher Timeframe MA Cross Strategy is a versatile trading tool designed to identify trend by utilizing two customizable moving averages (MAs) across different timeframes and types. This strategy includes detailed entry and exit rules with fully configurable inputs, offering flexibility to suit various trading styles.
Key Features:
- Two moving averages (MA1 and MA2) with customizable types, lengths, sources, and timeframes.
- Both long and short trade setups based on MA crossovers.
- Integrated risk management with adjustable stop-loss and take-profit levels based on a user-defined risk-to-reward (RTR) ratio.
- Clear visualization of MAs, entry points, stop-loss, and take-profit zones.
Inputs:
1. Risk-to-Reward Ratio (RTR):
- Defines the take-profit level in relation to the stop-loss distance. Default is 2.
2. MA1 Settings:
- Source: Select the data source for calculating MA1 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA1 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA1 calculation. Default is 20.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA1 to merge gaps. Default is true.
3. MA2 Settings:
- Source: Select the data source for calculating MA2 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA2 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA2 calculation. Default is 50.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA2 to merge gaps. Default is true.
Entry Rules:
- Long Entry:
- Triggered when MA1 crosses above MA2 (crossover).
- Entry is confirmed only when the bar is closed and no existing position is active.
- Short Entry:
- Triggered when MA1 crosses below MA2 (crossunder).
- Entry is confirmed only when the bar is closed and no existing position is active.
Exit Rules:
- Stop-Loss:
- For long positions: Set at the low of the bar preceding the entry.
- For short positions: Set at the high of the bar preceding the entry.
- Take-Profit:
- For long positions: Calculated as (Entry Price - Stop-Loss) * RTR + Entry Price.
- For short positions: Calculated as Entry Price - (Stop-Loss - Entry Price) * RTR.
Visualization:
- Plots MA1 and MA2 on the chart with distinct colors for easy identification.
- Highlights stop-loss and take-profit levels using shaded zones for clear visual representation.
- Displays the entry level for active positions.
This strategy provides a robust framework for traders to identify and act on trend reversals while maintaining strict risk management. The flexibility of its inputs allows for seamless customization to adapt to various market conditions and trading preferences.
