Enhanced Gap Up/Down AnalysisThis Pine Script indicator, titled "Enhanced Gap Up/Down Analysis", is designed to visually analyze the percentage gaps between the current day's opening price and the previous day's closing price. It provides valuable insights into market behavior by categorizing gaps and coloring them based on specific conditions.
Key Features:
Bar Coloring Based on Conditions:
Gap-Up Days:
Green if the day closes higher than it opens.
Red if the day closes lower than it opens.
Gap-Down Days:
Red if the day closes lower than it opens.
Green if the day closes higher than it opens.
The bar's position reflects the gap percentage (positive values for gap-ups above the X-axis, negative values for gap-downs below the X-axis).
Gap Size Thresholds:
Users can define small and moderate gap thresholds to categorize gaps:
Small Gaps: Transparent color.
Moderate Gaps: Opaque color.
Large Gaps: Fully visible color.
Ensures small gaps are less than moderate gaps with validation logic.
Filter Gaps by Percentage:
Includes filters to show gaps only within a user-defined range (minFilterGap to maxFilterGap).
Histogram Visualization:
Plots the gap percentages as a histogram for easy visual analysis:
Positive bars for gap-ups.
Negative bars for gap-downs.
Alerts for Large Gaps:
Alerts notify when a gap exceeds the moderate threshold in either direction.
Use Cases:
Identify Market Sentiment:
Quickly assess whether gap-ups or gap-downs dominate.
Analyze whether gaps tend to follow through or reverse by observing bar colors.
Filter Relevant Gaps:
Focus on significant gaps (e.g., only gaps greater than 2%).
Visual Aid for Trading:
Helps traders detect patterns in market gaps and price movement relationships (e.g., gaps and reversals).
Customizable Inputs:
Small and Moderate Gap Thresholds: Define gap categories.
Gap Filter Range: Control which gaps to display.
Alerts: Get notified of significant gaps.
This tool is particularly useful for traders analyzing price gaps and their implications for market trends or reversals.
지표 및 전략
Overnight Effect High Volatility Crypto (AiBitcoinTrend)👽 Overview of the Strategy
This strategy leverages the overnight effect in the cryptocurrency market, specifically targeting the two-hour window from 21:00 UTC to 23:00 UTC. The strategy is designed to be applied only during periods of high volatility, which is determined using historical volatility data. This approach, inspired by research from Padyšák and Vojtko (2022), aims to capitalize on statistically significant return patterns observed during these hours.
Deep Backtesting with a High Volatility Filter
Deep Backtesting without a High Volatility Filter
👽 How the Strategy Works
Volatility Calculation:
Each day at 00:00 UTC, the strategy calculates the 30-day historical volatility of crypto returns (typically Bitcoin). The historical volatility is the standard deviation of the log returns over the past 30 days, representing the market's recent volatility level.
Median Volatility Benchmark:
The median of the 30-day historical volatility is calculated over a 365-day period (one year). This median acts as a benchmark to classify each day as either:
👾 High Volatility: When the current 30-day volatility exceeds the median volatility.
👾 Low Volatility: When the current 30-day volatility is below the median.
Trading Rule:
If the day is classified as a High Volatility Day, the strategy executes the following trades:
👾 Buy at 21:00 UTC.
👾 Sell at 23:00 UTC.
Trade Execution Details:
The strategy uses a 0.02% fee per trade.
Each trade is executed with 25% of the available capital. This allocation helps manage risk while allowing for compounding returns.
Rationale:
The returns during the 22:00 and 23:00 UTC hours have been found to be statistically significant during high volatility periods. The overnight effect is believed to drive this phenomenon due to the asynchronous closing hours of global financial markets. This creates unique trading opportunities in the cryptocurrency market, where exchanges remain open 24/7.
👽 Market Context and Global Time Zone Impact
👾 Why 21:00 to 23:00 UTC?
During this window, major traditional financial markets are closed:
NYSE (New York) closes at 21:00 UTC.
London and European markets are closed during these hours.
Asian markets (Tokyo, Hong Kong, etc.) open later, leaving this window largely unaffected by traditional trading flows.
This global market inactivity creates a period where significant moves can occur in the cryptocurrency market, particularly during high volatility.
👽 Strategy Parameters
Volatility Period: 30 days.
The lookback period for calculating historical volatility.
Median Period: 365 days.
The lookback period for calculating the median volatility benchmark.
Entry Time: 21:00 UTC.
Adjust this to your local time if necessary (e.g., 16:00 in New York, 22:00 in Stockholm).
Exit Time: 23:00 UTC.
Adjust this to your local time if necessary (e.g., 18:00 in New York, 00:00 midnight in Stockholm).
👽 Benefits of the Strategy
Seasonality Effect:
The strategy captures consistent patterns driven by the overnight effect and high volatility periods.
Risk Reduction:
Since trades are executed during a specific window and only on high volatility days, the strategy helps mitigate exposure to broader market risk.
Simplicity and Efficiency:
The strategy is moderately complex, making it accessible for traders while offering significant returns.
Global Applicability:
Suitable for traders worldwide, with clear guidelines on adjusting for local time zones.
👽 Considerations
Market Conditions: The strategy works best in a high-volatility environment.
Execution: Requires precise timing to enter and exit trades at the specified hours.
Time Zone Adjustments: Ensure you convert UTC times accurately based on your location to execute trades at the correct local times.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Linear Regression Channel [TradingFinder] Existing Trend Line🔵 Introduction
The Linear Regression Channel indicator is one of the technical analysis tool, widely used to identify support, resistance, and analyze upward and downward trends.
The Linear Regression Channel comprises five main components : the midline, representing the linear regression line, and the support and resistance lines, which are calculated based on the distance from the midline using either standard deviation or ATR.
This indicator leverages linear regression to forecast price changes based on historical data and encapsulates price movements within a price channel.
The upper and lower lines of the channel, which define resistance and support levels, assist traders in pinpointing entry and exit points, ultimately aiding better trading decisions.
When prices approach these channel lines, the likelihood of interaction with support or resistance levels increases, and breaking through these lines may signal a price reversal or continuation.
Due to its precision in identifying price trends, analyzing trend reversals, and determining key price levels, the Linear Regression Channel indicator is widely regarded as a reliable tool across financial markets such as Forex, stocks, and cryptocurrencies.
🔵 How to Use
🟣 Identifying Entry Signals
One of the primary uses of this indicator is recognizing buy signals. The lower channel line acts as a support level, and when the price nears this line, the likelihood of an upward reversal increases.
In an uptrend : When the price approaches the lower channel line and signs of upward reversal (e.g., reversal candlesticks or high trading volume) are observed, it is considered a buy signal.
In a downtrend : If the price breaks the lower channel line and subsequently re-enters the channel, it may signal a trend change, offering a buying opportunity.
🟣 Identifying Exit Signals
The Linear Regression Channel is also used to identify sell signals. The upper channel line generally acts as a resistance level, and when the price approaches this line, the likelihood of a price decrease increases.
In an uptrend : Approaching the upper channel line and observing weakness in the uptrend (e.g., declining volume or reversal patterns) indicates a sell signal.
In a downtrend : When the price reaches the upper channel line and reverses downward, this is considered a signal to exit trades.
🟣 Analyzing Channel Breakouts
The Linear Regression Channel allows traders to identify price breakouts as strong signals of potential trend changes.
Breaking the upper channel line : Indicates buyer strength and the likelihood of a continued uptrend, often accompanied by increased trading volume.
Breaking the lower channel line : Suggests seller dominance and the possibility of a continued downtrend, providing a strong sell signal.
🟣 Mean Reversion Analysis
A key concept in using the Linear Regression Channel is the tendency for prices to revert to the midline of the channel, which acts as a dynamic moving average, reflecting the price's equilibrium over time.
In uptrends : Significant deviations from the midline increase the likelihood of a price retracement toward the midline.
In downtrends : When prices deviate considerably from the midline, a return toward the midline can be used to identify potential reversal points.
🔵 Settings
🟣 Time Frame
The time frame setting enables users to view higher time frame data on a lower time frame chart. This feature is especially useful for traders employing multi-time frame analysis.
🟣 Regression Type
Standard : Utilizes classical linear regression to draw the midline and channel lines.
Advanced : Produces similar results to the standard method but may provide slightly different alignment on the chart.
🟣 Scaling Type
Standard Deviation : Suitable for markets with stable volatility.
ATR (Average True Range) : Ideal for markets with higher volatility.
🟣 Scaling Coefficients
Larger coefficients create broader channels for broader trend analysis.
Smaller coefficients produce tighter channels for precision analysis.
🟣 Channel Extension
None : No extension.
Left: Extends lines to the left to analyze historical trends.
Right : Extends lines to the right for future predictions.
Both : Extends lines in both directions.
🔵 Conclusion
The Linear Regression Channel indicator is a versatile and powerful tool in technical analysis, providing traders with support, resistance, and midline insights to better understand price behavior. Its advanced settings, including time frame selection, regression type, scaling options, and customizable coefficients, allow for tailored and precise analysis.
One of its standout advantages is its ability to support multi-time frame analysis, enabling traders to view higher time frame data within a lower time frame context. The option to use scaling methods like ATR or standard deviation further enhances its adaptability to markets with varying volatility.
Designed to identify entry and exit signals, analyze mean reversion, and assess channel breakouts, this indicator is suitable for a wide range of markets, including Forex, stocks, and cryptocurrencies. By incorporating this tool into your trading strategy, you can make more informed decisions and improve the accuracy of your market predictions.
Nifty Top Gainers/Losers [ar]Nifty Top Gainers/Losers - Real-time Market Performance Tracker
A powerful indicator that monitors and displays real-time performance of 40 major Nifty stocks in a clean, organized table format. Perfect for traders seeking instant market breadth insights.
Key Features:
• Dynamic advances/declines counter at the top
• Real-time percentage change calculations
• Color-coded display (green for gainers, red for losers)
• Customizable reference points (Previous Day Close/Today's Open)
• Optional background color based on market breadth
• Flexible top gainers/losers limit setting
Customization Options:
- Adjust colors for gainers and losers
- Set transparency for background
- Modify the number of top performers to display
- Add/remove symbols from the watchlist
- Choose calculation reference (Previous Day Close/Today's Open)
Ideal for:
- Day traders monitoring market momentum
- Investors tracking sector rotation
- Analysts studying market breadth
- Portfolio managers seeking quick market overview
This indicator helps identify market leaders and laggards at a glance, making it an essential tool for informed trading decisions.
Multiple Moving Average Deviation Composite IndicatorMulti-Moving Average Deviation Comprehensive Indicator
Indicator Name
Multi-Moving Average Deviation Comprehensive Indicator (Short Title: Multi-MA Deviation Indicator)
**Design Concept**
This indicator is based on the deviation rates of multiple Exponential Moving Averages (EMA) to analyze market trends, overbought/oversold regions, and potential buy/sell signals. By visualizing comprehensive deviations and MACD-like signals, it provides intuitive market dynamics and deeper insights into price behavior through divergence detection.
Logic and Implementation Details
1. **Calculation of Multiple EMAs**
- Four user-defined periods (default: 20, 50, 100, 200) are used to calculate EMAs.
- Each EMA reflects the price trend over a specific timeframe.
2. **Deviation Rate Calculation**
- **Types of Deviation:**
- Deviation between closing price and EMA20:
$dif20 = \frac{close}{EMA20} \times 100 - 100$
- Deviation between EMA20 and EMA50:
$dif25 = \frac{EMA20}{EMA50} \times 100 - 100$
- Deviation between EMA50 and EMA100:
$dif51 = \frac{EMA50}{EMA100} \times 100 - 100$
- Deviation between EMA100 and EMA200:
$dif120 = \frac{EMA100}{EMA200} \times 100 - 100$
- Comprehensive Deviation Indicator (difxx):
Combines the above deviations with equal weighting to reflect the overall trend deviation.
3. **Trend Determination**
- If the comprehensive deviation (`difxx`) is positive, the market is in an uptrend.
- If `difxx` is negative, the market is in a downtrend.
4. **MACD-Like Dynamic Analysis**
- Computes the Simple Moving Average (SMA) and Exponential Moving Average (EMA) of the comprehensive deviation (`difxx`) to generate MACD-like signals.
- The histogram difference reflects market momentum changes.
- Histogram crossing from negative to positive triggers a buy signal, while crossing from positive to negative triggers a sell signal.
5. **Overbought and Oversold Regions**
- Defines dynamic overbought (`difmax`) and oversold (`difmin`) levels based on historical lowest and highest values of `difxx`.
- Values above `difmax` indicate an overbought region, and values below `difmin` indicate an oversold region.
6. **Divergence Detection**
- **Bearish Divergence:** Price makes a new high, but `difxx` does not.
- **Bullish Divergence:** Price makes a new low, but `difxx` does not.
- Divergence signals are marked on the chart for clarity.
7. **Trend Labels**
- Displays the current trend state (uptrend, downtrend, or sideways) on the chart.
How to Use
Parameter Settings
- Users can customize the following parameters to adapt to different market conditions:
- EMA periods (default: 20, 50, 100, 200)
- Length for calculating overbought and oversold levels (default: 200)
Key Signals
1. **Buy Signal**
- Triggered when the MACD histogram crosses from negative to positive.
- Buy signals in the oversold region are more reliable.
2. **Sell Signal**
- Triggered when the MACD histogram crosses from positive to negative.
- Sell signals in the overbought region carry higher risk.
3. **Trend Determination**
- Background color indicates the current trend:
- **Green Background:** Uptrend.
- **Red Background:** Downtrend.
4. **Divergence Signals**
- Bullish divergence suggests potential upward reversals.
- Bearish divergence suggests potential downward reversals.
Application Scenarios
- **Short-Term Trading:** Capture short-term reversals using overbought/oversold signals.
- **Trend Following:** Use `difxx` to identify trends and confirm them with MACD momentum.
- **Divergence Analysis:** Spot turning points in the market.
Notes
1. **Market Adaptability:**
- This indicator works best in trending markets but may produce false signals in sideways markets.
2. **Parameter Optimization:**
- Adjust EMA periods and divergence detection windows based on the characteristics of the asset being traded.
3. **Combination with Other Tools:**
- Enhance results by combining this indicator with other technical tools, such as Bollinger Bands or RSI.
This indicator allows traders to grasp market trends clearly, identify trading opportunities, and gain a deeper understanding of market behavior.
**多重移动平均线辑与使用说明**
**设计思路**
本指标基于多个指数移动平均线（EMA）的偏差率计算，用以分析市场的趋势、超买超卖区域、以及潜在的买卖信号。通过综合偏差和类似 MACD 的信号直观展现市场动态，并通过背离检测提供更深层次的价格行为洞察。
**逻辑与实现细节**
1. **多周期 EMA 计算**
- 使用四个用户自定义周期（默认分别为 20、50、100、200）计算 EMA。
- 每条 EMA 表示不同时间范围的价格趋势。
2. **偏差率计算**
- **偏差类型：**
- 收盘价与 EMA20 的偏差：$dif20 = \frac{close}{EMA20} \times 100 - 100$
- EMA20 与 EMA50 的偏差：$dif25 = \frac{EMA20}{EMA50} \times 100 - 100$
- EMA50 与 EMA100 的偏差：$dif51 = \frac{EMA50}{EMA100} \times 100 - 100$
- EMA100 与 EMA200 的偏差：$dif120 = \frac{EMA100}{EMA200} \times 100 - 100$
- 综合偏差指标（difxx）：对上述偏差赋予等权重并加总，用于反映综合趋势偏离程度。
3. **趋势判定**
- 若综合偏差 `difxx` 为正，则市场处于上升趋势。
- 若综合偏差 `difxx` 为负，则市场处于下降趋势。
4. **类似 MACD 的动态分析**
- 计算综合偏差的简单移动平均线（SMA）与指数移动平均线（EMA），形成类似 MACD 的信号。
- 差值直方图表示市场动能变化。
- 直方图由负转正触发买入信号，由正转负触发卖出信号。
5. **超买和超卖区域**
- 根据历史综合偏差最低和最高值定义动态超买（difmax）和超卖（difmin）水平。
- 超过 difmax 为超买区域，低于 difmin 为超卖区域。
6. **背离检测**
- **看跌背离：**价格创新高，但 `difxx` 没有创新高。
- **看涨背离：**价格创新低，但 `difxx` 没有创新低。
- 背离信号通过图形标记提示。
7. **趋势标签**
- 显示当前趋势状态（上升趋势、下降趋势或横向盘整）在图表上。
**使用方法**
**参数设置**
- 用户可调整以下参数以适应不同市场条件：
- EMA 周期（默认 20、50、100、200）
- 超买和超卖计算的参考长度（默认 200）
**主要信号**
1. **买入信号**
- 当 MACD 直方图由负转正，标记为“买入信号”。
- 超卖区域中出现买入信号具有更高可信度。
2. **卖出信号**
- 当 MACD 直方图由正转负，标记为“卖出信号”。
- 超买区域中出现卖出信号风险较高。
3. **趋势判断**
- 图表背景颜色指示当前趋势方向：
- **绿色背景：**上升趋势。
- **红色背景：**下降趋势。
4. **背离信号**
- 看涨背离提示可能的趋势反转向上。
- 看跌背离提示可能的趋势反转向下。
**应用场景**
- **短线交易：**结合超买超卖信号捕捉短期反转。
- **趋势跟踪：**利用 difxx 趋势判断并结合 MACD 动能确认趋势延续。
- **背离分析：**用于捕捉市场转折点。
**注意事项**
1. **市场适应性：**
- 指标适用于趋势明显的市场，震荡行情中可能出现较多虚假信号。
2. **参数优化：**
- 建议根据交易标的特性调整 EMA 周期与背离检测窗口长度。
3. **配合使用：**
- 与其他技术分析工具（如布林带、RSI）结合使用效果更佳。
通过此指标，交易者可以清晰掌握市场趋势、发现买卖机会，并更全面地理解市场行为。
指标若是有什么BUG或者建议请广大粉丝留言评论。
Master Litecoin Network Value Model BandThe "Master Litecoin Network Value Model Band" is a TradingView Pine Script indicator designed to analyze and visualize Litecoin's valuation dynamics in comparison to Bitcoin, leveraging a range of on-chain and market metrics. The script creates bands to highlight overvalued or undervalued conditions for Litecoin relative to multiple network and market factors.
Key Features:
Data Integration:
Incorporates on-chain data such as total addresses, new addresses, active addresses, transactions, volume, hodlers, and block sizes for both Litecoin and Bitcoin.
Uses market metrics like price, supply, and retail involvement to model Litecoin's network value.
Value Models:
Constructs individual models based on specific metrics (e.g., new addresses, transaction volume, median volume) to evaluate Litecoin's network valuation against Bitcoin.
Normalizes these models by adjusting for relative supply and Bitcoin's USD price.
Average and Median Models:
Calculates an Average Value Model by combining multiple metric-based models.
Provides a smoothed Median Value Model for more stable trends over time.
Dynamic Bands:
Identifies the maximum and minimum values among the various models to establish upper and lower bands for Litecoin's valuation.
Compares Litecoin's USD price to these bands, categorizing it as overvalued (above the upper band), undervalued (below the lower band), or fairly valued (within the bands).
Visual Representation:
Plots the upper and lower bounds (maxValue and minValue) along with Litecoin's price (ltcusd).
Highlights price movements with color-coded fills:
White fill: Litecoin price exceeds the maximum band.
Blue fill: Litecoin price is between the maximum and minimum bands.
Black fill: Litecoin price falls below the minimum band.
Purpose:
This indicator provides traders and analysts with a comprehensive tool to:
Assess Litecoin's market position relative to its network fundamentals.
Identify potential buy or sell zones based on deviation from fair valuation bands.
Track Litecoin's value trends in relation to Bitcoin as a benchmark.
Fibonacci Confluence Toolkit [LuxAlgo]The Fibonacci Confluence Toolkit is a technical analysis tool designed to help traders identify potential price reversal zones by combining key market signals and patterns. It highlights areas of interest where significant price action or reactions are anticipated, automatically applies Fibonacci retracement levels to outline potential pullback zones, and detects engulfing candle patterns.
Its unique strength lies in its reliance solely on price patterns, eliminating the need for user-defined inputs, ensuring a robust and objective analysis of market dynamics.
🔶 USAGE
The script begins by detecting CHoCH (Change of Character) points—key indicators of shifts in market direction. This script integrates the principles of pure price action as applied in Pure-Price-Action-Structures , where further details on the detection process can be found.
The detected CHoCH points serve as the foundation for defining an Area of Interest (AOI), a zone where significant price action or reactions are anticipated.
As new swing highs or lows emerge within the AOI, the tool automatically applies Fibonacci retracement levels to outline potential retracement zones. This setup enables traders to identify areas where price pullbacks may occur, offering actionable insights into potential entries or reversals.
Additionally, the toolkit highlights engulfing candle patterns within these zones, further refining entry points and enhancing confluence for better-informed trading decisions based on real-time trend dynamics and price behavior.
🔶 SETTINGS
🔹 Market Patterns
Bullish Structures: Enable or disable all bullish components of the indicator.
Bearish Structures: Enable or disable all bearish components of the indicator.
Highlight Area of Interest: Toggle the option to highlight the Areas of Interest (enabled or disabled).
CHoCH Line: Choose the line style for the CHoCH (Solid, Dashed, or Dotted).
Width: Adjust the width of the CHoCH line.
🔹 Retracement Levels
Choose which Fibonacci retracement levels to display (e.g., 0, 0.236, 0.382, etc.).
🔹 Swing Levels & Engulfing Patterns
Swing Levels: Select how swing levels are marked (symbols like ◉, △▽, or H/L).
Engulfing Candle Patterns: Choose which engulfing candle patterns to detect (All, Structure-Based, or Disabled).
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Gauti Market Maker Killzone EMA1. Identifying the Trend
Use Daily (1D) and Hourly (1H) Exponential Moving Averages (EMAs) to define the overall trend:
Bullish Trend: Both 1D and 1H EMAs are upward sloping, and the price is above these EMAs.
Bearish Trend: Both 1D and 1H EMAs are downward sloping, and the price is below these EMAs.
2. Confirmation with Higher Timeframes
Bullish Conditions:
Check 1D and 4H charts for price action above the EMA bands.
Look for price forming higher highs and higher lows or respecting support at the EMA bands.
Bearish Conditions:
Check 1D and 4H charts for price action below the EMA bands.
Look for price forming lower highs and lower lows or respecting resistance at the EMA bands.
Note: Crossover of EMAs on higher timeframes is an optional extra confirmation, but not mandatory for entry.
3. Entry Strategy
Use the 15-Minute (15M) timeframe for entries.
Entries are taken only during Killzones:
Killzones: London Open, New York Open, or other intraday key trading sessions. (Define the time ranges for these zones based on your trading hours.)
Wait for the price to touch or pull back to the EMA band during the Killzones in the direction of the overall trend:
In a bullish trend, enter long when the price touches the EMA band and shows signs of rejection or reversal.
In a bearish trend, enter short when the price touches the EMA band and shows signs of rejection or reversal.
4. Checklist for Entry
Confirm the following before entering:
1D Trend aligns with the 1H Trend.
Price Action in 1D and 4H supports the trend.
Killzone session is active.
Price is reacting to the EMA band on the 15M chart in the trend direction.
Asset Correlation CheckThis indicator evaluates how your current chart symbol interacts with key markets such as stock indices NASDAQ:NDX SP:SPX AMEX:IWM XETR:DAX PEPPERSTONE:CN50 , commodities CAPITALCOM:GOLD CAPITALCOM:SILVER , bonds NASDAQ:TLT NASDAQ:SHY , and cryptocurrencies BINANCE:BTCUSD , and displays the results in a compact, interactive table. It allows you to adjust the analysis period and select one of three correlation calculation methods (Index, Relative, and Beta) to gain different perspectives on the relationships between assets.
Index Correlation
Advantages: Provides a classic statistical correlation value, making it easy to understand overall directional alignment.
Drawbacks: Less reliable for highly volatile or short-term conditions, as temporary spikes can distort the correlation.
When to use: Ideal if you want a clear overview of whether two markets generally move together, for example to assess diversification effects.
Relative Correlation
Advantages: Focuses on percentage changes rather than absolute prices, offering a more dynamic view of short-term shifts.
Drawbacks: More prone to noise due to emphasizing daily or intra-period fluctuations.
When to use: Useful for timing-sensitive strategies, helping you quickly identify if one asset consistently outpaces or lags another in the short run.
Beta Correlation
Advantages: Examines how strongly one asset responds to changes in another, factoring in volatility and sensitivity, helpful for risk profiling.
Drawbacks: More abstract since it does not convey simple directional similarity but how intensely an asset reacts to market movements.
When to use: Ideal if you need to understand how a security may amplify or dampen broader market-level shifts, aiding in portfolio risk management.
Additionally, a Bull-Market Filter narrows the analysis to upward-trending phases, potentially delivering more meaningful insights. The indicator also computes average correlation values over your selected period, so you are not misled by brief fluctuations. It shows the percentage of positive versus negative readings to reveal if markets generally move in tandem or counter to each other.
For stock pickers, this tool is particularly valuable. It helps determine whether individual equities follow broader market forces, move with specific sectors, or behave independently. With this knowledge, you can refine stock selection, balance sector exposures, and seek opportunities that complement existing positions.
The indicator also facilitates the detection of patterns and anomalies, enabling early recognition of shifts in sentiment or new trend impulses. By visualizing how benchmarks, commodities, bonds, and digital assets relate, you gain deeper insight into key drivers that influence your investments.
Regarding rapid changes in correlation, keep in mind that correlation can frequently flip between positive and negative. Such volatility can create confusion if you rely on single readings. One moment, two assets may seem perfectly aligned; the next, they diverge. This does not necessarily indicate a lack of an underlying pattern; short-term factors can distort the picture. By looking at averages and the frequency of positive and negative occurrences, you confirm whether a correlation trend is genuine or simply a result of temporary noise. In other words, these additional metrics ensure that short-lived swings do not overshadow the true, longer-term relationship between the assets.
In essence, this indicator condenses complex intermarket analysis into a practical resource. By leveraging its insights, you can make data-driven decisions, adapt strategies to evolving market conditions, and lay a stronger foundation for long-term trading success.
Psychological Levels- Rounding Numbers Psychological Levels Indicator
Overview:
The Psychological Levels Indicator automatically identifies and plots significant price levels based on psychological thresholds, which are key areas where market participants often focus their attention. These levels act as potential support or resistance zones due to human behavioral tendencies to round off numbers. This indicator dynamically adjusts the levels based on the stock's price range and ensures seamless visibility across the chart.
Key Features:
Dynamic Step Sizes:
The indicator adjusts the levels dynamically based on the stock price:
For prices below 500: Levels are spaced at 10.
For prices between 500 and 3000: Levels are spaced at 50, 100, and 1000.
For prices between 3000 and 10,000: Levels are spaced at 100 and 1000.
For prices above 10,000: Levels are spaced at 500 and 1000.
Extended Visibility:
The plotted levels are extended across the entire chart for improved visualization, ensuring traders can easily monitor these critical zones over time.
Customization Options:
Line Color: Choose the color for the levels to suit your charting style.
Line Style: Select from solid, dashed, or dotted lines.
Line Width: Adjust the thickness of the lines for better clarity.
Clean and Efficient Design:
The indicator only plots levels relevant to the visible chart range, avoiding unnecessary clutter and ensuring a clean workspace.
How It Works:
It calculates the relevant step sizes based on the price:
Smaller step sizes for lower-priced stocks.
Larger step sizes for higher-priced stocks.
Primary, secondary, and (if applicable) tertiary levels are plotted dynamically:
Primary Levels: The most granular levels based on the stock price.
Secondary Levels: Higher-order levels for broader significance.
Tertiary Levels: Additional levels for lower-priced stocks to enhance detail.
These levels are plotted across the chart, allowing traders to visualize key psychological areas effortlessly.
Use Cases:
Day Trading: Identify potential intraday support and resistance levels.
Swing Trading: Recognize key price zones where trends may pause or reverse.
Long-Term Investing: Gain insights into significant price zones for entry or exit strategies.
Hilega-Milega-RSI-EMA-WMA indicator designed by NKThis indicator is works on RSI, Price and volume to give leading Indicator to Buy or Sell.
This indicator works on all financial markets
Hilega-Milega-RSI-EMA-WMA indicator designed by Nitish Sir
For intraday trade, enter with 15 mins chart.
For positional trade, enter with 1-hour chart.
For Investment this system can be used with daily/weekly/monthly chart.
• RED line is for Volume.
• Green line is for the Price.
• Black line is for the RSI (9).
SELL Trade
1. When Volume (RED line) is above/crossed above Price (Green line) and Strength (Black line), then stock price will go down. This means we will SELL.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Oversold zone OR Red line cross over the Green and black line then we will exit.
In case of the SELL trade, after the entry we will monitor the trade in 5 min chart, if the candle is closed above the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
BUY Trade
1. When Volume (RED line) is below/crossed below Price (Green line) and Strength (Black line), then stock price will go up. This means we will BUY.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Overbought zone OR Red line cross over the Green and black line then we will exit.
In case of the Buy trade, after the entry we will monitor the trade candle is closed below the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
Multi-Indicator Signal with TableThis indicator is a versatile multi-indicator tool designed for traders who want to combine signals from various popular indicators into a single framework. It not only visualizes buy and sell signals but also provides a clear, easy-to-read table that summarizes the included indicators and their respective signal colors.
Key Features:
RSI (Relative Strength Index):
Buy Signal: RSI falls below the oversold level (default: 30).
Sell Signal: RSI rises above the overbought level (default: 70).
Signal Color: Green.
MACD (Moving Average Convergence Divergence):
Buy Signal: MACD line crosses above the signal line.
Sell Signal: MACD line crosses below the signal line.
Signal Color: Blue.
MA Crossover (Moving Average Crossover):
Buy Signal: Short EMA (default: 7) crosses above Long SMA (default: 14).
Sell Signal: Short EMA crosses below Long SMA.
Signal Color: Purple.
Stochastic Oscillator:
Buy Signal: Stochastic %K falls below 20 and crosses above %D.
Sell Signal: Stochastic %K rises above 80 and crosses below %D.
Signal Color: Yellow.
TSI (True Strength Index):
Buy Signal: TSI crosses above the zero line.
Sell Signal: TSI crosses below the zero line.
Signal Color: Red.
Dynamic Signal Table:
A clean, compact table displayed at the top-right corner of the chart, summarizing the indicators and their respective signal colors for quick reference.
Customization:
All indicator parameters are fully adjustable, allowing users to fine-tune settings to match their trading strategy.
Signal colors and table design ensure a visually intuitive experience.
Usage:
This tool is ideal for traders who prefer a multi-indicator approach for generating buy/sell signals.
The combination of different indicators helps to filter out noise and increase the accuracy of trade setups.
Notes:
Signals appear only after the confirmation of the current bar to avoid false triggers.
This indicator is designed for educational purposes and should be used in conjunction with proper risk management strategies.
BTC Dominance/Price vs Alts Logic (QKWESI)BTC Dominance & Price vs. Alts Indicator
Overview: The BTC Dominance & Price vs. Alts indicator is designed to help cryptocurrency traders understand the relationship between Bitcoin's market dominance, its price movements, and the subsequent impact on altcoin trends. By analyzing these key metrics, the indicator provides actionable insights to inform trading decisions.
Key Features:
BTC Dominance Tracking: Monitors Bitcoin's dominance percentage to assess its influence over the crypto market.
Real-Time BTC Price: Displays the latest Bitcoin price movements for informed analysis.
Alts Trend Prediction: Predicts altcoin behavior—such as Pump, Dump, Stable, or Increase—based on the combined trends of BTC Dominance and BTC Price.
Color-Coded Table: Presents data in a structured table with color indicators for easy interpretation.
Trend Indicators: Utilizes clear symbols to represent the direction of each metric, aiding quick decision-making.
Logic Table:
BTC Dominance BTC Price Alts Result
Increases Increases Decrease
Increases Decreases Dump
Increases Stable Stable
Decreases Increases Pump
Decreases Decreases Stable
Decreases Stable Increase
Explanation:
Increases in BTC Dominance & Increases in BTC Price: Altcoins are likely to Decrease in value.
Increases in BTC Dominance & Decreases in BTC Price: Altcoins may Dump, experiencing a sharp drop.
Increases in BTC Dominance & Stable BTC Price: Altcoins are expected to remain Stable.
Decreases in BTC Dominance & Increases in BTC Price: Altcoins may Pump, gaining significant value.
Decreases in BTC Dominance & Decreases in BTC Price: Altcoins are likely to remain Stable.
Decreases in BTC Dominance & Stable BTC Price: Altcoins may Increase moderately.
Benefits:
Informed Trading Decisions: Leverage BTC metrics to anticipate altcoin movements.
Efficient Market Analysis: Quickly assess market conditions without multiple indicators.
Structured Insights: The color-coded table and trend indicators provide a clear overview of key market dynamics.
Custom Sign [Alert + Marker]Custom Sign
An indicator that detects crossovers between two values and displays them with customizable markers and colors on your TradingView chart.
Key Features
Detection of crossover, crossunder, and cross (both) events
Two display modes: Oscillator and Indicator
Customizable markers and colors
Bar-close alerts
Settings
Source Settings
Source 1: Select the first value to compare
Cross Type: Select cross type (⏫up, ⏬down, 🔀both)
Source 2: Select the second value to compare
Oscillator Side
Use Unified Signal: Toggle unified marker
Unified: Shape for unified marker
CrossOver: Marker for upward cross
CrossUnder: Marker for downward cross
Location: Marker position (Top/Bottom/Invisible)
Indicator Side
Use Unified Signal: Toggle unified marker
Unified: Shape for unified marker
CrossOver: Marker for upward cross
CrossUnder: Marker for downward cross
Location: Marker position (Auto/Top/Bottom/AboveBar/BelowBar/Invisible)
Color Settings
Oscillator
* Use Unified Color: Toggle single color mode
* Unified: Color for unified mode
* CrossOver: Color for upward cross
* CrossUnder: Color for downward cross
Indicator
* Use Unified Color: Toggle single color mode
* Unified: Color for unified mode
* CrossOver: Color for upward cross
* CrossUnder: Color for downward cross
Alert Settings
Alert Message: Customize alert message
Notes
Oscillator and Indicator sides can be configured independently
Different markers and colors can be used for each side
Alerts trigger once per bar at close
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
👽 Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
👽 Deep Dive into the Core Mathematics
👾 Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
👾 Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
👾 k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
👾 Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
👽 AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
👽 Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
RShar Liquidity Zone Identifier Description of the Liquidity Zone Identifier Indicator
The **Liquidity Zone Identifier** is a TradingView indicator designed to highlight key liquidity zones on a price chart. Liquidity zones represent areas where the price is likely to encounter significant resistance or support, making them critical for technical analysis and trading decisions.
Key Features:
1. **Dynamic Resistance and Support Levels**:
- The indicator calculates the highest high and lowest low over a user-defined period (`length`) to identify potential resistance and support levels.
- Sensitivity can be adjusted using the `zoneSensitivity` parameter, which defines a percentage buffer around these levels to expand the zones.
2. **Visual Representation**:
- Resistance zones are highlighted in **red**, indicating areas where the price may face selling pressure.
- Support zones are highlighted in **green**, representing areas where the price may find buying interest.
- The zones are displayed as shaded regions using the `fill` function, making them visually distinct and easy to interpret.
3. **Customizable Inputs**:
- **Zone Length** (`length`): Determines the number of candles considered for calculating highs and lows.
- **Zone Sensitivity** (`zoneSensitivity`): Sets the percentage margin around the calculated levels to define the liquidity zones.
- **Zone Colors**: Users can customize the colors for resistance and support zones to suit their preferences.
- **Toggle Fill**: The `showFill` option allows users to enable or disable shaded zone visualization.
4. **Alerts for Trading Opportunities**:
- Alerts are triggered when:
- The price enters the **resistance zone** (current high is greater than or equal to the resistance zone).
- The price enters the **support zone** (current low is less than or equal to the support zone).
- These alerts help traders stay informed of critical market movements without constantly monitoring the chart.
#### How It Works:
1. **Calculation of Zones**:
- The highest high and lowest low over the specified `length` are calculated to define the primary levels.
- A buffer zone is added around these levels based on the `zoneSensitivity` percentage, creating a margin of interaction for price movements.
2. **Plotting the Zones**:
- The top and bottom boundaries of the resistance and support zones are plotted as lines.
- The area between these boundaries is shaded using the `fill` function to enhance visualization.
3. **Alerts for Key Events**:
- Traders are notified when price action interacts with the zones, enabling quick decision-making.
#### Use Case:
The Liquidity Zone Identifier is ideal for:
- Identifying areas of potential price reversal or consolidation.
- Spotting high-probability trading setups near resistance and support zones.
- Complementing other technical indicators in a trading strategy.
By effectively highlighting critical price levels, this indicator provides traders with a powerful tool to navigate the markets with greater precision.
Resistance & SupportThis indicator combines multiple analytical methods to calculate potential support and resistance levels for the upcoming trading day, leveraging historical price data. The calculations are based on three key areas:
Pivot Points: These are calculated using the previous day's high, low, and close values to provide central price levels, along with first and second-level support and resistance (S1, S2, R1, R2). These levels are commonly used in technical analysis and can serve as reference points for market entries and exits.
3-Day Price Average (3DBP): This value provides a short-term trend signal by averaging the high, low, and close prices over the past three days. The indicator helps identify whether the market has been trading at higher or lower levels recently, which can signal bullish or bearish trends.
Trend Detection: The script also includes a short-term and long-term trend analysis:
Short-Term Trend: The prior day’s 3DBP is compared to the previous day’s 3DBP to gauge the market's short-term direction.
Long-Term Trend: The prior close is compared to the open from 50 days ago, offering an indication of the overall market trend.
These components work together to provide actionable insights on potential entry points. For example:
In a bullish market, support levels may act as potential entry points for long trades when the price retraces.
In a bearish market, resistance levels may act as potential entry points for short trades upon price rejection.
The Trend Table at the top right of the chart displays the short-term and long-term trend information for quick reference. It shows whether the trends are bullish or bearish based on the calculations above.
While originally optimized for the EUR/USD currency pair, this indicator can be applied to other forex pairs. However, results may vary depending on the instrument, and further testing is recommended for non-EUR/USD pairs.
Usage Notes:
Pivot points can often act as both support and resistance. While they provide useful reference levels, in volatile markets, these levels may not always hold. Tight stop-losses are recommended if trading near these levels.
The 3DBP offers insight into past market behavior, and although it’s not guaranteed to act as support or resistance, it can help identify zones of interest in the short term.
This indicator is designed to provide a structured approach to price action analysis, incorporating widely-recognized methods like pivot points and trend detection, while adding unique elements like the 3DBP to enhance its utility.
Option vs Index Performance**Indicator Name:** Option vs Index Performance
**Description:**
This indicator helps traders analyze the relative performance of options compared to their underlying index (e.g., Nifty 50). It evaluates and highlights zones based on two key metrics:
1. **Bar-to-Bar Performance:** Compares the percentage movement of the option price against the index movement on a bar-by-bar basis.
- **Green Zone**: Option outperforms the index.
- **Yellow Zone**: Option moves in sync with the index.
- **Red Zone**: Option underperforms the index.
2. **Swing Alignment:** Tracks the swing structure of the index (higher highs, higher lows) and compares it with the option chart. The indicator checks if the option's swings align with or deviate from the index's swing pattern.
The final output combines both conditions, providing clear visual zones below the chart:
- **Green**: Overperformance and alignment with the index.
- **Yellow**: Neutral performance or partial alignment.
- **Red**: Underperformance or misalignment with the index.
Use this tool on option charts to quickly identify opportunities and assess whether the option's movement is in line with the broader market trend.
Ticker Tape with Multiple Inputs# Ticker Tape
A customizable multi-symbol price tracker that displays real-time price information in a scrolling ticker format, similar to financial news tickers.
This indicator is inspired from Tradingciew's default tickertape indicator with changes in the way inputs are given.
### Overview
This indicator allows you to monitor up to 15 different symbols simultaneously across any supported exchanges on TradingView. It displays essential price information including current price, price change, and percentage change in an easy-to-read format at the bottom of your chart.
### Features
• Monitor up to 15 different symbols simultaneously
• Support for any exchange available on TradingView
• Real-time price updates
• Color-coded price changes (green for increase, red for decrease)
• Smooth scrolling animation (can be disabled)
• Customizable scroll speed and position offset
### Input Parameters
#### Ticker Tape Controls
• Running: Enable/disable the scrolling animation
• Offset: Adjust the starting position of the ticker tape
#### Symbol Settings
• Exchange (1-15): Enter the exchange name (e.g., NSE, BINANCE, NYSE)
• Symbol (1-15): Enter the symbol name (e.g., BANKNIFTY, RELIANCE, BTCUSDT)
### Display Format
For each symbol, the ticker shows:
1. Symbol Name
2. Current Price
3. Price Change (Absolute and Percentage)
### Example Usage
Input Settings:
Exchange 1: NSE
Symbol 1: BANKNIFTY
Exchange 2: NSE
Symbol 2: RELIANCE
The ticker tape will display:
`NIFTY BANK 46750.00 +350.45 (0.75%) | RELIANCE 2456.85 -12.40 (-0.50%) |`
### Use Cases
1. Multi-Market Monitoring: Track different markets simultaneously without switching between charts
2. Portfolio Tracking: Monitor all your positions in real-time
### Tips for Best Use
1. Group related symbols together for easier monitoring
2. Use the offset parameter to position important symbols in your preferred viewing area
3. Disable scrolling if you prefer a static display
4. Leave exchange field empty for default exchange symbols
### Notes
• Price updates occur in real-time during market hours
• Color coding helps quickly identify price direction
• The indicator adapts to any chart timeframe
• Empty input pairs are automatically skipped
### Performance Considerations
The indicator is optimized for efficiency, but monitoring too many high-frequency symbols might impact chart performance. It's recommended to use only the symbols you actively need to monitor.
Version: 2.0 Stock_Cloud
Last Updated: December 2024
Financial Conditions Composite Z-Score1. Inputs and Data Sources
The script pulls data for the following financial metrics using TradingView's request.security function:
CBOE:VIX (Volatility Index): A measure of market volatility.
MOVE Index: A measure of bond market volatility (or Treasury volatility).
BAMLH0A0HYM2 (High-Yield Spread): The spread between high-yield corporate bonds and Treasury yields.
BAMLC0A0CM (Credit Spread): The spread for investment-grade corporate bonds.
Each of these metrics represents a key aspect of financial conditions:
VIX: Equity market risk.
MOVE: Bond market risk.
High-Yield Spread and Credit Spread: Perception of risk in corporate debt.
2. Z-Score Calculation
A z-score standardizes each metric to show how far it deviates from its average over a specified period (lookback = 160, or 160 days):
Positive z-scores indicate the metric is higher than average.
Negative z-scores indicate the metric is lower than average.
The formula for the z-score:
Z-Score = Metric − Mean
Standard Deviation Z-Score = Standard Deviation Metric−Mean
3. Combined Z-Score
The script combines the four individual z-scores into a single Composite Z-Score, equally weighted across the metrics:
Combined Z-Score = (Z VIX + Z MOVE + Z High-Yield Spread + Z Credit Spread) / 4
This Combined Z-Score provides an overall measure of financial conditions:
Positive combined z-scores indicate tighter or riskier financial conditions.
Negative combined z-scores indicate looser or less risky financial conditions.
4. Visual Elements on the Chart
A. Colorful Lines: Individual Z-Scores
Each of the four metrics is plotted as a separate line:
Red: Z-score of the VIX.
Green: Z-score of the MOVE index.
Orange: Z-score of the high-yield spread.
Purple: Z-score of the credit spread.
These lines show how each metric contributes to the overall financial conditions. For example:
A rising red line means increasing equity market volatility (risk).
A rising green line means increasing bond market volatility (risk).
B. Blue Line: Combined Z-Score
The blue line represents the Combined Z-Score. It aggregates the individual z-scores into a single measure:
A rising blue line suggests financial conditions are tightening (greater risk across markets).
A falling blue line suggests financial conditions are loosening (lower risk across markets).
C. Red and Green Background: Z-Score Regions
Red Background: When the Combined Z-Score is positive (>0), it indicates riskier or tighter financial conditions.
Green Background: When the Combined Z-Score is negative (<0), it indicates less risky or looser financial conditions.
This background coloring helps visually distinguish periods of riskier financial conditions from less risky ones.
5. Purpose of the Visualization
This indicator provides a comprehensive view of financial conditions across multiple asset classes:
Traders can use it to gauge the level of systemic market stress.
Investors can use it to assess when risk is elevated (positive z-scores) or subdued (negative z-scores).
It helps in decision-making for strategies that depend on market volatility or risk appetite.
Summary of What You See:
Colorful Lines (Red, Green, Orange, Purple): Individual z-scores for each metric (VIX, MOVE, high-yield spread, credit spread).
Blue Line: The aggregated Combined Z-Score that summarizes financial conditions.
Red and Green Background:
Red: Tight or risky financial conditions (Combined Z-Score > 0).
Green: Loose or low-risk financial conditions (Combined Z-Score < 0).
This visualization provides a multi-dimensional view of financial conditions at a glance, helping to identify periods of high or low risk in the markets.
Bollinger Bands Volatility Arrows
Explanation of Changes:
Arrow Style:
Green Up Arrow (▲): Indicates increasing volatility with a positive value.
Red Down Arrow (▼): Indicates decreasing volatility with a negative value.
Labels with Arrows:
label.new is used to create arrows with the label.style_label_up or label.style_label_down styles.
The numerical value of the volatility is displayed beside the arrow using str.tostring.
Label Position:
For increasing volatility, the green arrow is placed near the high of the candle.
For decreasing volatility, the red arrow is placed near the low of the candle.
Text Format:
Includes the arrow symbol and the volatility value (formatted to 4 decimal places).
How It Works:
You’ll see green upward arrows for increasing volatility and red downward arrows for decreasing volatility.
Each arrow includes the exact value of the Bollinger Bands width at that moment.
VWAP Trend with Standard Deviation & MidlinesThis indicator is a sophisticated VWAP (Volume Weighted Average Price) tool with multiple features:
Core Functionality:
1. Calculates a primary VWAP line that changes color based on trend direction (green when rising, red when falling)
2. Creates multiple standard deviation bands around the VWAP at customizable distances
3. Resets calculations at either:
- New York session start time (configurable, default 9:30 AM)
- Daily start time
- Can be hidden on daily/weekly/monthly timeframes if desired
Band Structure:
- Band 1 (innermost): ±1 standard deviation
- Band 2 (middle): ±2 standard deviations
- Band 3 (outermost): ±3 standard deviations
- Midlines at 0.5σ intervals between bands
- All bands can be individually enabled/disabled
Customization Options:
1. Band calculation modes:
- Standard Deviation based
- Percentage based
2. Visual settings:
- Customizable colors for all elements
- Adjustable line widths
- Optional labels with configurable size
- Optional extension lines
- Label position adjustment
3. Source data selection (default: HLC3 - High, Low, Close average)
Common Uses:
- Identifying potential support/resistance levels
- Measuring price volatility
- Spotting mean reversion opportunities
- Trading range analysis
- Trend direction confirmation
The indicator essentially creates a dynamic support/resistance structure that adapts to market volatility and volume, making it useful for both intraday and swing trading strategies.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
