Spot Premium with ROCDescription:
This indicator tracks the spot premium of BTC by comparing the perpetual futures price (perp) from Binance against the spot price on Coinbase. The histogram displays the price difference (spot minus perp) with green bars when spot is higher and red when perp carries a premium. The Rate of Change (ROC) line measures how quickly this premium shifts, with an option to normalize fluctuations for greater stability.
Implications & Possible Use Cases:
• Market Sentiment Gauge: A sustained positive premium often indicates bullish sentiment, while a discount can signal bearish bias.
• Arbitrage Signals: Significant divergences between perp and spot may present short-term arbitrage opportunities across exchanges.
• Risk Management & Hedging: Traders can align derivatives and spot positions when premiums deviate sharply, reducing funding cost exposures.
• Funding Rate Insights: Since perp funding rates tend to follow premium levels, this indicator can act as an early warning for funding spikes.
• Trend Confirmation: Use the normalized ROC to confirm continuation or reversal of premium trends, filtering out noise around small diff values.
Let me know if you would like additional features.
Поиск скриптов по запросу "sentiment"
MÈGAS ALGO : CNA (Cognitio Analysis) [INDICATOR]Overview
The CNA (Cognitio Analysis) is a comprehensive financial analysis tool designed to evaluate the overall health and potential of a market or company based on fundamental metrics. It aggregates data across five key metric groups—**Growth**, **Profitability**, **Cash Flow**, **Income**, and **Valuation**—to provide a final interpretation of market conditions. The indicator dynamically adapts to the selected fiscal period (Quarter, Year, or Trailing Twelve Months) and delivers insights into dominant trends and conflicting signals.
Key Features
1. Customizable Fiscal Period:
- Users can select between "Quarter", "Year", or "Trailing Twelve Months" (TTM) to analyze data for their desired timeframe.
2. Dynamic Table Visualization:
- Displays raw metric values, aggregated scores, and the final interpretation in an intuitive
table.
- Highlights the final interpretation with dynamic background colors (`color.teal` for bullish,
`color.red` for bearish, etc.).
3. Comprehensive Data Integration:
- Pulls financial data using TradingView's `request.financial()` function for metrics like
revenue, earnings, margins, and valuation ratios.
4. Normalization and Scoring:
- Normalizes data to create a consistent scoring system, ensuring accurate comparisons across
metrics.
How It Works
1. Metric Group Analysis
- Growth Metrics: Measures revenue growth, earnings per share (EPS) growth, and tax
efficiency.
- Profitability Metrics: Analyzes net profit margin, return on equity (ROE), and EBITDA margin.
- Cash Metrics: Assesses operating cash flow margin, free cash flow to operating cash flow
ratio, and cash flow coverage.
- Income Metrics: Examines gross profit margin, operating profit margin, and EBIT margin.
- Valuation Metrics: Evaluates price-to-earnings (P/E), price-to-sales (P/S), and enterprise
value-to-EBITDA (EV/EBITDA).
2. Dynamic Scoring System
- Metrics are normalized to ensure consistency across different scales.
- A geometric mean is used to calculate scores for each metric group, ensuring that all metrics
within a group contribute equally to the final score.
3. Dominant Trend Identification
- Scores from all five metric groups are aggregated to determine the **dominant trend** of the
market.
- The dominant trend is categorized as:
- Bullish: Strong fundamentals across most metrics.
- Bearish: Weak fundamentals across most metrics.
- Neutral: Balanced conditions with no clear direction.
- Unclear: Mixed signals dominate, requiring further monitoring.
4. Conflicting Signals Interpretation
- The indicator identifies scenarios where metrics conflict (e.g., high growth but low valuation).
- These conflicting signals provide nuanced insights into market conditions, highlighting rare opportunities or potential risks.
How to Use the Indicator
1. Select Fiscal Period:
- Choose between "FQ", "FY", or "TTM" to analyze data for the desired timeframe.
2. Review Metric Scores:
- Examine the scores for each metric group (Growth, Profitability, Cash, Income, Valuation) to
understand the underlying performance.
3. Interpret Final Output:
- The final interpretation provides a summary of the dominant trend and conflicting signals,
helping users make informed decisions.
4. Dynamic Coloring:
- Use the dynamic background colors in the table to quickly identify market sentiment
(bullish, bearish, neutral, or mixed).
Applications
- Identifying Opportunities:
- Look for bullish dominant trends combined with undervalued growth opportunities for
potential long positions.
- Avoiding Risks:
- Watch out for bearish dominant trends with overvaluation alerts to avoid potential losses.
- Monitoring Neutral Markets:
- Use the indicator to identify neutral markets and wait for clearer signals before making
decisions.
Conclusion
The CNA (Cognitio Analysis) is a powerful tool for traders and investors seeking to make informed decisions based on fundamental analysis. By combining detailed metric evaluations, dynamic scoring, and sentiment-based interpretations, this indicator provides a comprehensive view of market conditions. Whether you're identifying undervalued opportunities, avoiding overvalued risks, or monitoring neutral markets, this indicator equips you with the insights needed to navigate complex financial landscapes.
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outc
NY ORB, VWAP & EMAsIndicator is designed to display key technical analysis tools on your Trading View chart. It includes:
One of the key benefits of this indicator is that it allows Basic Trading View users to set VWAP, EMAs, and ORB in a single indicator. This is particularly useful for users who are limited to a single indicator on their Basic plan, as it provides a comprehensive view of market sentiment, trend, and potential breakouts without the need for multiple indicators.
Features
New York Opening Range Breakout (ORB): Plots the high and low of the first 15 minutes (configurable) of the New York trading session.
Volume Weighted Average Price (VWAP): Displays the VWAP line, which can be toggled on or off.
Exponential Moving Averages (EMAs): Plots four EMAs (9, 21, 50, and 200 periods), which can also be toggled on or off.
Customization
ORB Length: Choose from 5 or 15 minutes for the ORB calculation.
Show VWAP and EMAs: Toggle the visibility of the VWAP and EMA lines on or off.
Usage
This indicator is designed to help traders identify key market levels, trends, and potential breakouts during the New York trading session. The ORB can be used to gauge market sentiment, while the VWAP provides a benchmark for average price action. The EMAs offer additional trend analysis and can be used to identify potential support and resistance levels.
FOMO Indicator - % of Stocks Above 5-Day AvgThe FOMO Indicator plots the breadth indicators NCFD and S5FD below the price chart, representing the percentage of stocks in the Nasdaq Composite (NCFD) or S&P 500 (S5FD) trading above their respective 5-day moving averages.
This indicator identifies short-term market sentiment and investor positioning. When over 85% of stocks exceed their 5-day averages, it signals widespread buying pressure and potential FOMO (Fear Of Missing Out) among investors. Conversely, levels below 15% may indicate oversold conditions. By analyzing these breadth metrics over a short time window, the FOMO Indicator helps traders gauge shifts in investor sentiment and positioning.
Volume Stack US Top 40 [Pt]█ Overview
Volume Stack US Top 40 is a versatile TradingView indicator designed to give you an at-a-glance view of market sentiment and volume dynamics across the top 40 U.S. large-cap stocks. Inspired by the popular Saty Volume Stack, this enhanced version aggregates essential volume and price strength data from major tickers on both the NYSE and NASDAQ, and works seamlessly on all timeframes.
█ Key Features
Dynamic Buy / Sell Volume Stack: This indicator dynamically stacks the volume bars so that the side with higher volume appears on top. For example, green over red signals more buy-side volume, while red over green indicates greater sell-side volume.
Cross-Market Analysis: Easily toggle between NYSE and NASDAQ to analyze the most influential U.S. stocks. The indicator automatically loads the correct set of tickers based on your selection.
Flexible Coverage: Choose from Top 10, Top 20, Top 30, or Top 40 tickers to tailor the tool to your desired scope of analysis.
Dynamic Table Display: A neat on-chart table lists the selected ticker symbols along with visual cues that reflect each stock’s strength. You can even remove exchange prefixes for a cleaner look.
█ Inputs & Settings
Market Selector: Choose whether to view data from the NYSE or NASDAQ; the indicator automatically loads the corresponding list of top tickers.
Number of Tickers: Select from ‘Top 10’, ‘Top 20’, ‘Top 30’, or ‘Top 40’ stocks to define the breadth of your analysis.
Color Options: Customize the colors for bullish and bearish histogram bars to suit your personal style.
Table Preferences: Adjust the on-chart table’s display style (grid or one row), text size, and decide whether to show exchange information alongside ticker symbols.
█ Usage & Benefits
Volume Stack US Top 40 is ideal for traders and investors who need a clear yet powerful tool to gauge overall market strength. By combining volume and price action data across multiple major stocks, it helps you:
Quickly assess whether the market sentiment is bullish or bearish.
Confirm trends by comparing volume patterns against intraday price movements.
Enhance your trading decisions with a visual representation of market breadth and dynamic buy/sell volume stacking.
Its intuitive design means you spend less time adjusting complex settings and more time making confident, informed decisions.
Salience Theory Crypto Returns (AiBitcoinTrend)The Salience Theory Crypto Returns Indicator is a sophisticated tool rooted in behavioral finance, designed to identify trading opportunities in the cryptocurrency market. Based on research by Bordalo et al. (2012) and extended by Cai and Zhao (2022), it leverages salience theory—the tendency of investors, particularly retail traders, to overemphasize standout returns.
In the crypto market, dominated by sentiment-driven retail investors, salience effects are amplified. Attention disproportionately focused on certain cryptocurrencies often leads to temporary price surges, followed by reversals as the market stabilizes. This indicator quantifies these effects using a relative return salience measure, enabling traders to capitalize on price reversals and trends, offering a clear edge in navigating the volatile crypto landscape.
👽 How the Indicator Works
Salience Measure Calculation :
👾 The indicator calculates how much each cryptocurrency's return deviates from the average return of all cryptos over the selected ranking period (e.g., 21 days).
👾 This deviation is the salience measure.
👾 The more a return stands out (salient outcome), the higher the salience measure.
Ranking:
👾 Cryptos are ranked in ascending order based on their salience measures.
👾 Rank 1 (lowest salience) means the crypto is closer to the average return and is more predictable.
👾 Higher ranks indicate greater deviation and unpredictability.
Color Interpretation:
👾 Green: Low salience (closer to average) – Trending or Predictable.
👾 Red/Orange: High salience (far from average) – Overpriced/Unpredictable.
👾 Text Gradient (Teal to Light Blue): Helps visualize potential opportunities for mean reversion trades (i.e., cryptos that may return to equilibrium).
👽 Core Features
Salience Measure Calculation
The indicator calculates the salience measure for each cryptocurrency by evaluating how much its return deviates from the average market return over a user-defined ranking period. This measure helps identify which assets are trending predictably and which are likely to experience a reversal.
Dynamic Ranking System
Cryptocurrencies are dynamically ranked based on their salience measures. The ranking helps differentiate between:
Low Salience Cryptos (Green): These are trending or predictable assets.
High Salience Cryptos (Red): These are overpriced or deviating significantly from the average, signaling potential reversals.
👽 Deep Dive into the Core Mathematics
Salience Theory in Action
Salience theory explains how investors, particularly in the crypto market, tend to prefer assets with standout returns (salient outcomes). This behavior often leads to overpricing of assets with high positive returns and underpricing of those with standout negative returns. The indicator captures these deviations to anticipate mean reversions or trend continuations.
Salience Measure Calculation
// Calculate the average return
avgReturn = array.avg(returns)
// Calculate salience measure for each symbol
salienceMeasures = array.new_float()
for i = 0 to array.size(returns) - 1
ret = array.get(returns, i)
salienceMeasure = math.abs(ret - avgReturn) / (math.abs(ret) + math.abs(avgReturn) + 0.1)
array.push(salienceMeasures, salienceMeasure)
Dynamic Ranking
Cryptos are ranked in ascending order based on their salience measures:
Low Ranks: Cryptos with low salience (predictable, trending).
High Ranks: Cryptos with high salience (unpredictable, likely to revert).
👽 Applications
👾 Trend Identification
Identify cryptocurrencies that are currently trending with low salience measures (green). These assets are likely to continue their current direction, making them good candidates for trend-following strategies.
👾 Mean Reversion Trading
Cryptos with high salience measures (red to light blue) may be poised for a mean reversion. These assets are likely to correct back towards the market average.
👾 Reversal Signals
Anticipate potential reversals by focusing on high-ranked cryptos (red). These assets exhibit significant deviation and are prone to price corrections.
👽 Why It Works in Crypto
The cryptocurrency market is dominated by retail investors prone to sentiment-driven behavior. This leads to exaggerated price movements, making the salience effect a powerful predictor of reversals.
👽 Indicator Settings
👾 Ranking Period : Number of bars used to calculate the average return and salience measure.
Higher Values: Smooth out short-term volatility.
Lower Values: Make the ranking more sensitive to recent price movements.
👾 Number of Quantiles : Divide ranked assets into quantile groups (e.g., quintiles).
Higher Values: More detailed segmentation (deciles, percentiles).
Lower Values: Broader grouping (quintiles, quartiles).
👾 Portfolio Percentage : Percentage of the portfolio allocated to each selected asset.
Enter a percentage (e.g., 20 for 20%), automatically converted to a decimal (e.g., 0.20).
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.
Correlation Coefficient [Giang]### **Introduction to the "Correlation Coefficient" Indicator**
#### **Idea behind the Indicator**
The "Correlation Coefficient" indicator was developed to analyze the linear relationship between Bitcoin (**BTCUSD**) and other important economic indices or financial assets, such as:
- **SPX** (S&P 500 Index): Represents the U.S. stock market.
- **DXY** (Dollar Index): Reflects the strength of the USD against major currencies.
- **SPY** (ETF representing the S&P 500): A popular trading instrument.
- **GOLD** (Gold price): A traditional safe-haven asset.
The correlation between these assets can help traders understand how Bitcoin reacts to market movements of traditional financial instruments, providing opportunities for more effective trading decisions.
Additionally, the indicator allows users to **customize asset symbols for comparison**, not limited to the default indices (SPX, DXY, SPY, GOLD). This flexibility enables traders to tailor their analysis to specific goals and portfolios.
---
#### **Significance and Use of Correlation in Trading**
**Correlation** is a measure of the linear relationship between two data series. In the context of this indicator:
- **The correlation coefficient ranges from -1 to 1**:
- **1**: Perfect positive relationship (both increase or decrease together).
- **0**: No linear relationship.
- **-1**: Perfect negative relationship (one increases while the other decreases).
- **Use in trading**:
- Identify **strong relationships or unusual divergences** between Bitcoin and other assets.
- Help determine **market sentiment**: For example, if Bitcoin has a negative correlation with DXY, traders might expect Bitcoin to rise when the USD weakens.
- Provide a foundation for hedging strategies or investments based on inter-asset relationships.
---
#### **Components of the Indicator**
The "Correlation Coefficient" indicator consists of the following key components:
1. **Main Data (BTCUSD)**:
- The closing price of Bitcoin is used as the central asset for calculations.
2. **Comparison Data**:
- Users can select different asset symbols for comparison. By default, the indicator supports:
- **SPX**: Stock market index.
- **DXY**: Dollar Index.
- **SPY**: Popular ETF.
- **GOLD**: Gold price.
3. **Correlation Coefficients**:
- Calculated between BTC and each comparison index, based on a Weighted Moving Average (WMA) over a user-defined period.
4. **Graphical Representation**:
- Displays individual correlation coefficients with each comparison index, making it easier for traders to track and analyze.
---
#### **How to Analyze and Use the Indicator**
**1. Identify Key Correlations:**
- Observe the correlation lines between BTC and the indices to determine positive or negative relationships.
- Example:
- If the **Correlation Coefficient (BTC-DXY)** sharply declines to -1, this indicates that when USD strengthens, Bitcoin tends to weaken.
**2. Analyze the Strength of Correlations:**
- **Strong Correlations**: If the coefficient is close to 1 or -1, the relationship between the two assets is very clear.
- **Weak Correlations**: If the coefficient is near 0, Bitcoin may be influenced by other factors outside the compared index.
**3. Develop Trading Strategies:**
- Use correlations to predict Bitcoin's price movements:
- If BTC has an inverse relationship with **DXY**, traders might consider selling BTC when the USD strengthens.
- If BTC and **SPX** are strongly correlated, traders can monitor the stock market to predict Bitcoin's trend.
**4. Evaluate Changes Over Time:**
- Use different timeframes (daily, weekly) to track the correlation's fluctuations.
- Look for unusual signals, such as a breakdown or shift from positive to negative relationships.
---
#### **Conclusion**
The "Correlation Coefficient" indicator is a powerful tool that helps traders analyze the relationship between Bitcoin and major financial indices. The ability to customize asset symbols for comparison makes the indicator flexible and suitable for various trading strategies. When used correctly, this indicator not only provides insights into market sentiment but also supports the development of intelligent trading strategies and optimized profits.
BTC CME Futures Divergence TrackerThis script tracks divergences between price action and open interest for the BTC CME Futures contract (symbol "BTC1!") using the following components:
Key Features:
1. Price Analysis: Identifies lower highs in the price over a specified lookback period. Marks these points with red upward-facing triangles above the bars.
2. Open Interest Analysis: Retrieves open interest (OI) data for the BTC CME Futures contract via request.security. Detects lower highs in open interest over the same lookback period. Highlights these points with blue downward-facing triangles below the bars.
3. Divergence Detection: A divergence is identified when both price and open interest form lower highs simultaneously. Highlights such occurrences with a purple background, indicating potential bearish sentiment or weakening momentum.
4. Alerts: If divergences are detected, an alert is triggered (if enabled), notifying the trader to take action.
5. Visualization: Open interest is plotted as a blue line in a separate pane for added context. Red and blue markers highlight significant points in price and open interest trends.
Use Cases:
- Spot Weakening Trends: Divergences between price and open interest may indicate a loss of momentum or bearish sentiment, allowing traders to preemptively adjust their strategies.
- Monitor Institutional Activity: Open interest changes reflect shifts in market participation, especially in derivative markets like CME Futures.
- Set Alerts for Key Signals: With automated alerts, traders can stay informed of potential divergence signals without constant monitoring.
Customization Options:
- Lookback Period: Adjust the number of bars used to detect lower highs.
- Timeframe: Choose the timeframe for fetching open interest data (e.g., daily, hourly).
- Alert Activation: Enable or disable alerts for divergences.
This tool combines price action with open interest dynamics to provide a robust method for identifying market trends and potential reversals in BTC CME Futures.
Value at Risk [OmegaTools]The "Value at Risk" (VaR) indicator is a powerful financial risk management tool that helps traders estimate the potential losses in a portfolio over a specified period of time, given a certain level of confidence. VaR is widely used by financial institutions, traders, and risk managers to assess the probability of portfolio losses in both normal and volatile market conditions. This TradingView script implements a comprehensive VaR calculation using several models, allowing users to visualize different risk scenarios and adjust their trading strategies accordingly.
Concept of Value at Risk
Value at Risk (VaR) is a statistical technique used to measure the likelihood of losses in a portfolio or financial asset due to market risks. In essence, it answers the question: "What is the maximum potential loss that could occur in a given portfolio over a specific time horizon, with a certain confidence level?" For instance, if a portfolio has a one-day 95% VaR of $10,000, it means that there is a 95% chance the portfolio will not lose more than $10,000 in a single day. Conversely, there is a 5% chance of losing more than $10,000. VaR is a key risk management tool for portfolio managers and traders because it quantifies potential losses in monetary terms, allowing for better-informed decision-making.
There are several ways to calculate VaR, and this indicator script incorporates three of the most commonly used models:
Historical VaR: This approach uses historical returns to estimate potential losses. It is based purely on past price data, assuming that the past distribution of returns is indicative of future risks.
Variance-Covariance VaR: This model assumes that asset returns follow a normal distribution and that the risk can be summarized using the mean and standard deviation of past returns. It is a parametric method that is widely used in financial risk management.
Exponentially Weighted Moving Average (EWMA) VaR: In this model, recent data points are given more weight than older data. This dynamic approach allows the VaR estimation to react more quickly to changes in market volatility, which is particularly useful during periods of market stress. This model uses the Exponential Weighted Moving Average Volatility Model.
How the Script Works
The script starts by offering users a set of customizable input settings. The first input allows the user to choose between two main calculation modes: "All" or "OCT" (Only Current Timeframe). In the "All" mode, the script calculates VaR using all available methodologies—Historical, Variance-Covariance, and EWMA—providing a comprehensive risk overview. The "OCT" mode narrows the calculation to the current timeframe, which can be particularly useful for intraday traders who need a more focused view of risk.
The next input is the lookback window, which defines the number of historical periods used to calculate VaR. Commonly used lookback periods include 21 days (approximately one month), 63 days (about three months), and 252 days (roughly one year), with the script supporting up to 504 days for more extended historical analysis. A longer lookback period provides a more comprehensive picture of risk but may be less responsive to recent market conditions.
The confidence level is another important setting in the script. This represents the probability that the loss will not exceed the VaR estimate. Standard confidence levels are 90%, 95%, and 99%. A higher confidence level results in a more conservative risk estimate, meaning that the calculated VaR will reflect a more extreme loss scenario.
In addition to these core settings, the script allows users to customize the visual appearance of the indicator. For example, traders can choose different colors for "Bullish" (Risk On), "Bearish" (Risk Off), and "Neutral" phases, as well as colors for highlighting "Breaks" in the data, where returns exceed the calculated VaR. These visual cues make it easy to identify periods of heightened risk at a glance.
The actual VaR calculation is broken down into several models, starting with the Historical VaR calculation. This is done by computing the logarithmic returns of the asset's closing prices and then using linear interpolation to determine the percentile corresponding to the desired confidence level. This percentile represents the potential loss in the asset over the lookback period.
Next, the script calculates Variance-Covariance VaR using the mean and standard deviation of the historical returns. The standard deviation is multiplied by a z-score corresponding to the chosen confidence level (e.g., 1.645 for 95% confidence), and the resulting value is subtracted from the mean return to arrive at the VaR estimate.
The EWMA VaR model uses the EWMA for the sigma parameter, the standard deviation, obtaining a specific dynamic in the volatility. It is particularly useful in volatile markets where recent price behavior is more indicative of future risk than older data.
For traders interested in intraday risk management, the script provides several methods to adjust VaR calculations for lower timeframes. By using intraday returns and scaling them according to the chosen timeframe, the script provides a dynamic view of risk throughout the trading day. This is especially important for short-term traders who need to manage their exposure during high-volatility periods within the same day. The script also incorporates an EWMA model for intraday data, which gives greater weight to the most recent intraday price movements.
In addition to calculating VaR, the script also attempts to detect periods where the asset's returns exceed the estimated VaR threshold, referred to as "Breaks." When the returns breach the VaR limit, the script highlights these instances on the chart, allowing traders to quickly identify periods of extreme risk. The script also calculates the average of these breaks and displays it for comparison, helping traders understand how frequently these high-risk periods occur.
The script further visualizes the risk scenario using a risk phase classification system. Depending on the level of risk, the script categorizes the market as either "Risk On," "Risk Off," or "Risk Neutral." In "Risk On" mode, the market is considered bullish, and the indicator displays a green background. In "Risk Off" mode, the market is bearish, and the background turns red. If the market is neither strongly bullish nor bearish, the background turns neutral, signaling a balanced risk environment.
Traders can customize whether they want to see this risk phase background, along with toggling the display of the various VaR models, the intraday methods, and the break signals. This flexibility allows traders to tailor the indicator to their specific needs, whether they are day traders looking for quick intraday insights or longer-term investors focused on historical risk analysis.
The "Risk On" and "Risk Off" phases calculated by this Value at Risk (VaR) script introduce a novel approach to market risk assessment, offering traders an advanced toolset to gauge market sentiment and potential risk levels dynamically. These risk phases are built on a combination of traditional VaR methodologies and proprietary logic to create a more responsive and intuitive way to manage exposure in both normal and volatile market conditions. This method of classifying market conditions into "Risk On," "Risk Off," or "Risk Neutral" is not something that has been traditionally associated with VaR, making it a groundbreaking addition to this indicator.
How the "Risk On" and "Risk Off" Phases Are Calculated
In typical VaR implementations, the focus is on calculating the potential losses at a given confidence level without providing an overall market outlook. This script, however, introduces a unique risk classification system that takes the output of various VaR models and translates it into actionable signals for traders, marking whether the market is in a Risk On, Risk Off, or Risk Neutral phase.
The Risk On and Risk Off phases are primarily determined by comparing the current returns of the asset to the average VaR calculated across several different methods, including Historical VaR, Variance-Covariance VaR, and EWMA VaR. Here's how the process works:
1. Threshold Setting and Effect Calculation: The script first computes the average VaR using the selected models. It then checks whether the current returns (expressed as a negative value to signify loss) exceed the average VaR value. If the current returns surpass the calculated VaR threshold, this indicates that the actual market risk is higher than expected, signaling a potential shift in market conditions.
2. Break Analysis: In addition to monitoring whether returns exceed the average VaR, the script counts the number of instances within the lookback period where this breach occurs. This is referred to as the "break effect." For each period in the lookback window, the script checks whether the returns surpass the calculated VaR threshold and increments a counter. The percentage of periods where this breach occurs is then calculated as the "effect" or break percentage.
3. Dual Effect Check (if "Double" Risk Scenario is selected): When the user chooses the "Double" risk scenario mode, the script performs two layers of analysis. First, it calculates the effect of returns exceeding the VaR threshold for the current timeframe. Then, it calculates the effect for the lower intraday timeframe as well. Both effects are compared to the user-defined confidence level (e.g., 95%). If both effects exceed the confidence level, the market is deemed to be in a high-risk situation, thus triggering a Risk Off phase. If both effects fall below the confidence level, the market is classified as Risk On.
4. Risk Phases Determination: The final risk phase is determined by analyzing these effects in relation to the confidence level:
- Risk On: If the calculated effect of breaks is lower than the confidence level (e.g., fewer than 5% of periods show returns exceeding the VaR threshold for a 95% confidence level), the market is considered to be in a relatively safe state, and the script signals a "Risk On" phase. This is indicative of bullish conditions where the potential for extreme loss is minimal.
- Risk Off: If the break effect exceeds the confidence level (e.g., more than 5% of periods show returns breaching the VaR threshold), the market is deemed to be in a high-risk state, and the script signals a "Risk Off" phase. This indicates bearish market conditions where the likelihood of significant losses is higher.
- Risk Neutral: If the break effect hovers near the confidence level or if there is no clear trend indicating a shift toward either extreme, the market is classified as "Risk Neutral." In this phase, neither bulls nor bears are dominant, and traders should remain cautious.
The phase color that the script uses helps visualize these risk phases. The background will turn green in Risk On conditions, red in Risk Off conditions, and gray in Risk Neutral phases, providing immediate visual feedback on market risk. In addition to this, when the "Double" risk scenario is selected, the background will only turn green or red if both the current and intraday timeframes confirm the respective risk phase. This double-checking process ensures that traders are only given a strong signal when both longer-term and short-term risks align, reducing the likelihood of false signals.
A New Way of Using Value at Risk
This innovative Risk On/Risk Off classification, based on the interaction between VaR thresholds and market returns, represents a significant departure from the traditional use of Value at Risk as a pure risk measurement tool. Typically, VaR is employed as a backward-looking measure of risk, providing a static estimate of potential losses over a given timeframe with no immediate actionable feedback on current market conditions. This script, however, dynamically interprets VaR results to create a forward-looking, real-time signal that informs traders whether they are operating in a favorable (Risk On) or unfavorable (Risk Off) environment.
By incorporating the "break effect" analysis and allowing users to view the VaR breaches as a percentage of past occurrences, the script adds a predictive element that can be used to time market entries and exits more effectively. This **dual-layer risk analysis**, particularly when using the "Double" scenario mode, adds further granularity by considering both current timeframe and intraday risks. Traders can therefore make more informed decisions not just based on historical risk data, but on how the market is behaving in real-time relative to those risk benchmarks.
This approach transforms the VaR indicator from a risk monitoring tool into a decision-making system that helps identify favorable trading opportunities while alerting users to potential market downturns. It provides a more holistic view of market conditions by combining both statistical risk measurement and intuitive phase-based market analysis. This level of integration between VaR methodologies and real-time signal generation has not been widely seen in the world of trading indicators, marking this script as a cutting-edge tool for risk management and market sentiment analysis.
I would like to express my sincere gratitude to @skewedzeta for his invaluable contribution to the final script. From generating fresh ideas to applying his expertise in reviewing the formula, his support has been instrumental in refining the outcome.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
MM Sector Intraday TrackerWhat this script does:
This script tracks the percent that price has moved from the opening print of each of the 9 sector ETFs. It color codes the values so you can see which sectors are down (red color) and which sectors are up (green color). If a sector is only up or down half of one ATR, it the color will be light, but if it is beyond half of one ATR, it is a darker color.
How this script works:
It simply measures the distance that price has moved from the opening print today, and presents that information in an easy to read table on your chart.
How to use this script:
If all sectors are moving in one direction, it indicates that the entire market is in a trend day in that direction. You can use this information to decide which direction you should be trading (ie. with trend). For example, in order for there to be healthy bullish moves in the market, you would want this indicator to show you that all sectors are green, or at least that some sectors are green, which would indicate that there is healthy rotation of capital across the market sectors.
What makes this script original:
Most indicators and even the TradingView watchlist measure the percent changed on the day from the closing price of a stock on the prior trading day, essentially telling you what sentiment is since yesterday. This script tells you the sentiment today since it is priced from the opening print.
Bearish vs Bullish ArgumentsThe Bearish vs Bullish Arguments Indicator is a tool designed to help traders visually assess and compare the number of bullish and bearish arguments based on their custom inputs. This script enables users to input up to five bullish and five bearish arguments, dynamically displaying the bias on a clean and customizable table on the chart. This provides traders with a clear, visual representation of the market sentiment they have identified.
Key Features:
Customizable Inputs: Users can input up to five bullish and five bearish arguments, which are displayed in a table on the chart.
Bias Calculation: The script calculates the bias (Bullish, Bearish, or Neutral) based on the number of bullish and bearish arguments provided.
Color Customization: Users can customize the colors for the table background, text, and headers, ensuring the table fits seamlessly into their charting environment.
Reset Functionality: A reset switch allows users to clear all input arguments with a single click, making it easy to start fresh.
How It Works:
Input Fields: The script provides input fields for up to five bullish and five bearish arguments. Each input is a simple text field where users can describe their arguments.
Bias Calculation: The script counts the number of non-empty bullish and bearish arguments and determines the overall bias. The bias is displayed in the table with a dynamically changing color to indicate whether the market sentiment is bullish, bearish, or neutral.
Customizable Table: The table is positioned on the chart according to the user's preference (top-left, top-right, bottom-left, bottom-right) and can be customized in terms of background color and text color.
How to Use:
Add the Indicator: Add the Bearish vs Bullish Arguments Indicator to your chart.
Input Arguments: Enter up to five bullish and five bearish arguments in the provided input fields in the script settings.
Customize Appearance: Adjust the table's background color, text color, and position on the chart to fit your preferences.
Example Use Case:
A trader might use this indicator to visually balance their arguments for and against a particular trade setup. By entering their reasons for a bullish outlook in the bullish argument fields and their reasons for a bearish outlook in the bearish argument fields, they can quickly see which side has more supporting points and make a more informed trading decision.
This script was inspired by Arjoio's concepts
Opening Range & Prior Day High/Low [Gorb]Introduction:
Opening Range & Prior Day High/Low indicator is an easy to use day traders tool. This indicator automatically plots the previous days high and low, as well as drawing a box from the opening range that the user specifies in the settings. These two together can help provide an indication of market sentiment and price trends for the day. They are often used as a trading strategy for day traders.
Overview:
The Opening Range , draws a box from the high to the low of the user defined time period and is extended until the end of the trading session. Most common are the 5/15/30min opening ranges.
Prior Day High/Low , draws lines from the previous days high and low that extend across the current session. These are used as support/resistance and also a marker to see market sentiment by crossing one of these levels.
The indicator is designed for all kinds of traders, offering a simple approach to automatically plot levels for you.
Features:
All skill-level friendly presets, easy to enable with one-click
Opening Range: Allows user to choose what time the range starts and ends to measure the high & low.
Extend Range Lines: allows the user to choose when the box stops extending according to the trading session time.
Enable Opening Range Box: allows the user to choose to plot the opening range or not.
ORB Border Color: allows the user to change the box border color.
ORB Box Shade Color: allows the user to change the background of the opening range box.
ORB Line Width: allows users to chose the width of the opening range box lines.
Enable Previous Day High: allows users to enable the previous days high to be plotted.
Enable Previous Day Low: allows users to enable the previous days high to be plotted.
Previous Day High Color: allows users to choose the color for this line.
Previous Day Low Color: allows users to choose the color for this line.
All colors are changeable for the user to customize to their liking.
Usage Demonstration
In the image below, we can see a basic example of how these 3 features function.
As explained above, the opening range is customizable to meet the users needs and can be disabled with one click. Same goes for the prior day high(green) and low(red) lines. All 3 are plotted each day automatically for the user if enabled.
In the image below, we can see an example of using the opening range break and prior day high together for a trading strategy.
This is a great example of using the prior day high with the opening range to use as a day trading strategy. It provides the trader with levels to watch for price to break out from for possible trade setups.
In this next image, we can see a failed breakdown from the opening range that results in a bullish breakout.
The first move was a fake breakdown with the failed rejection on the retest of the opening range lows. This led to a breakout above the range and a confirmation bounce on the breakout retest. Price did break above the prior day high and confirmed with a retest bounce on that level as well.
In the image below, we can see how previous days levels can act as resistance to use with the opening range.
Price didn't reject the opening range low, but it did reject the prior day high for the second time. This could be used as an entry or once price breaks down out of the opening range again.
Conclusion:
We believe in providing user-friendly tools to help speed up traders technical analysis and implement easy trading strategies. The goal is to provide a user-friendly indicator to automatically draw opening ranges and previous days levels to suit the users needs and trading style.
RISK DISCLAIMER
All content, tools, scripts & education provided by Monstanzer or Gorb Algo LLC are for informational & educational purposes only. Trading is risk and most lose their money, past performance does not guarantee future results.
Double Supertrend HTF FilterDouble Supertrend HTF Filter: A Comprehensive Market Direction Tool
The Double Supertrend HTF Filter is an innovative tool designed for traders who seek a more holistic view of market trends. At its core, the indicator combines two Supertrends from different higher timeframes, providing a layered perspective on the market's direction. Instead of juggling between multiple timeframes or charts, traders get a consolidated view with this indicator. One of its standout features is the horizontal line at the bottom of the chart, which visually represents the alignment of the two Supertrends – a simple yet powerful way to gauge the combined sentiment of the two higher timeframes on your chart.
The Supertrend Indicator: Origins and Rationale
The Supertrend indicator, a popular tool among traders, was developed by Olivier Seban. At its essence, the Supertrend is a trend-following indicator, designed to identify and visualize the current market trend. It operates using average true range (ATR) values and price data, effectively smoothing out market noise to present clearer trend directions. When prices move with a consistent momentum upwards or downwards, the Supertrend remains below or above the price respectively, signaling the prevailing trend's direction. The rationale behind the Supertrend is its ability to adapt to price volatility. By factoring in the average true range, it dynamically adjusts itself, ensuring that it's not just based on price but also the inherent volatility of the market. This adaptability makes it a valuable tool for traders, offering insights into potential trend reversals and potential entry or exit points.
Filter Usage
The main idea behind the Double Supertrend HTF is to use the indicator as a filter in addition to a signal indicator to your liking. To illustrate, consider incorporating it with a MACD Oscillator, such as the one detailed in this article: When the solid line at the bottom of the chart turns green, it signals that both supertrends are up and thus allows for long positions, indicating a bullish sentiment across both the chosen higher timeframes. Conversely, a red line permits short positions, hinting at a bearish trend. Should the line turn yellow, it's a sign of caution. The market is indecisive, and it might be prudent to refrain from taking any trades until a clearer direction emerges.
Features of the Indicator
Understanding that traders have different preferences, the Double Supertrend HTF Filter comes with customizable features. With the easy user interface you can change the timeframe, ATR and factor to your preferred trading strategy. The default settings are set for the 30 minutes and 4 hour timeframe, which is my personal preference for scalping trades on lower timeframes (eg. 1min, 5 min, 10 min, 15 min). While the dual Supertrend lines offer valuable insights, a chart can become cluttered when combined with other indicators. Therefore, traders have the option to toggle on or off the display of the Supertrends. This ensures that you have the flexibility to maintain a clean chart view while still benefiting from the insights the tool provides at the bottom of the chart.
A Note on Usage
It's essential to highlight that the Double Supertrend HTF Filter is for educational purposes. While it offers a unique perspective on market trends and can be a valuable addition to a trader's toolkit, it's merely an example of how one can use the Supertrend as a filter. Always conduct thorough research and consider your trading strategy before making any decisions.
If you have any comments or ideas how to combine this filter with other indicators feel free to leave a comment.
Odd_mod Econ CalendarA modification of Economic Calendar Events: FOMC, CPI, and more written by jdehorty . Please send all tips his way as he is maintaining the underlying data for the Calendar and the original concept.
List of changes:
Optimized code, will only run once on initialization now(No random line in middle of screen on bar change)
Legend - Added short names
Legend - Removed header
Legend - Made repositionable with selectable top margins
Legend - Removed data name from legend when it is disabled
Legend - Removed border
Original Description by jdehorty :
This script plots major events from the Economic Calendar that often correspond to major pivot points in various markets. It also includes built-in logic to retroactively adjust larger time intervals (i.e. greater than 1 hour) to be correctly aligned with the interval during which the event occurred.
Events are taken from the Economic Calendar and will be updated periodically at the following library:
EconomicCalendar
The above library can be used to conveniently access date-related data for major Meetings, Releases, and Announcements as integer arrays, which can be used in other indicators. Currently, it has support for the following events:
FOMC Meetings
The FOMC meets eight times a year to determine the course of monetary policy . The FOMC's decisions are based on a review of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
FOMC Minutes
The FOMC minutes are released three weeks after each FOMC meeting. The minutes provide a detailed account of the FOMC's discussion of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
Producer Price Index (PPI) Releases
The Producer Price Index (PPI) measures changes in the price level of goods and services sold by domestic producers. The PPI is a weighted average of prices of a basket of goods and services, such as transportation, food, and medical care. PPI is a leading indicator of CPI .
Consumer Price Index ( CPI ) Releases
The Consumer Price Index ( CPI ) measures changes in the price level of goods and services purchased by households. The CPI is a weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. CPI is one of the most widely used measures of inflation .
Consumer Sentiment Index ( CSI ) Releases
The University of Michigan's Consumer Sentiment Index ( CSI ) is a measure of consumer attitudes about the economy. The CSI is based on a monthly survey of U.S. households and reflects the consumers' assessment of present and future economic conditions. The CSI is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
Consumer Confidence Index ( CCI ) Releases
The Consumer Confidence Index is a survey that measures how optimistic or pessimistic consumers are regarding their expected financial situation.
Non-Farm Payroll (NFP) Releases
The Non-Farm Payroll (NFP) is a measure of the change in the number of employed persons, excluding farm workers and government employees. The NFP is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
Economic Calendar Events: FOMC, CPI, and moreThis script plots major events from the Economic Calendar that often correspond to major pivot points in various markets. It also includes built-in logic to retroactively adjust larger time intervals (i.e. greater than 1 hour) to be correctly aligned with the interval during which the event occurred.
Events are taken from the Economic Calendar and will be updated periodically at the following library:
The above library can be used to conveniently access date-related data for major Meetings, Releases, and Announcements as integer arrays, which can be used in other indicators. Currently, it has support for the following events:
FOMC Meetings
The FOMC meets eight times a year to determine the course of monetary policy. The FOMC's decisions are based on a review of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
FOMC Minutes
The FOMC minutes are released three weeks after each FOMC meeting. The minutes provide a detailed account of the FOMC's discussion of economic and financial developments and its assessment of the likely effects of these developments on the economic outlook.
Producer Price Index (PPI) Releases
The Producer Price Index (PPI) measures changes in the price level of goods and services sold by domestic producers. The PPI is a weighted average of prices of a basket of goods and services, such as transportation, food, and medical care. PPI is a leading indicator of CPI.
Consumer Price Index (CPI) Releases
The Consumer Price Index (CPI) measures changes in the price level of goods and services purchased by households. The CPI is a weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. CPI is one of the most widely used measures of inflation.
Consumer Sentiment Index (CSI) Releases
The University of Michigan's Consumer Sentiment Index (CSI) is a measure of consumer attitudes about the economy. The CSI is based on a monthly survey of U.S. households and reflects the consumers' assessment of present and future economic conditions. The CSI is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
Consumer Confidence Index (CCI) Releases
The Consumer Confidence Index is a survey that measures how optimistic or pessimistic consumers are regarding their expected financial situation.
Non-Farm Payroll (NFP) Releases
The Non-Farm Payroll (NFP) is a measure of the change in the number of employed persons, excluding farm workers and government employees. The NFP is a leading indicator of consumer spending, which accounts for about two-thirds of U.S. economic activity.
Blockchain Fundamentals - Active Address Sentiment Osc. [CR]Blockchain Fundamentals: Active Address Sentiment Oscillator AASO
Back with another script today, this one is a useful tool in helping to determine bitcoins value. We are looking at 2 data sources: the daily active addresses on the BTC blockchain, and the daily returns of BTC.
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
There is an interesting relationship that you can see by comparing the two timeseries. But for us to create a good indicator we first need to normalize the data. So we look at the percent change over the past 28 days for each metric (DAA and price).
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
We then calculate standard deviation bands around the DAA metric. We finalize them by averaging the bands over a 28 day period.
When the Price series (yellow line) is higher than the SD bands BTC is considered overvalued or price is overheated. A pullback could be expected soon. When the Price series is below the SD bands BTC is considered undervalued or price is oversold.
THIS INDICATOR WILL ONLY GIVE YOU THE CORRECT RESULTS ON THE DAILY TIMEFRAME
This tool doesnt give signals on the one minute chart or tell you exactly when to buy or sell. BUT what it does do is act as a convenient macro sentiment indicator that is not based completely upon price.
In an attempt to narrow down the really juicy areas, if you seen the background color highlights with white, that means its likely a top or bottom. At the very least on a local sense and many times in a cyclical macro sense as well. It also narrows down the signal to a generally more profitable area.
This indicator is not meant to be used on timeframes other than daily (did I mention that already?). I am lazy and did not code the calculations to be MTF (which is why you have to use on the daily chart). If you want to code this, please forward it on to me and I will post an update with a heartfelt credit to you.
RSI vs Longs/Shorts Margin Ratio Percentage RankThis indicator plots the RSI of the current token and the percentage rank, of the RSI, of the ratio of a long margined token to a short margined token.
By default it plots the RSI of the current token with a color based on percentage rank the RSI of BITFINEX:BTCUSDLONGS divided by BITFINEX:BTCUSDSHORTS, so the assumption is that you are using it on a BTC chart. While you can select any Tradingview symbol for your Long and Short tokens I don't think you will get meaningful results unless you select a long and short margined token that matches your chart symbol, such as BITFINEX:ETHUSDLONGS and BITFINEX:ETHUSDSHORTS if you're trading ETHUSD. Even using margined tokens the results may not be meaningful, if there is not enough trade volume in the token, or if they are being manipulated, so you must backtest everything.
The three plot options are:
• Colored RSI - RSI plotted with colors based on the Longs/Shorts ratio
• Background Color - White RSI plot with Longs/Shorts ratio as background color
• RSI + Ratio - White RSI with Longs/Shorts ratio plotted in color
The chart shows all three options on an hourly BITFINEX:SOLUSD chart with BITFINEX:SOLUSDSHORTS and BITFINEX:SOLUSDLONGS.
By default it also plots a short term moving average and it can also plot the raw ratio rather than the percentage rank if selected.
This script started out as "RSI vs BITFINEX BTC Longs/Shorts Margin Ratio Percentage Rank" by me. I was interested in the ratio of BITFINEX:BTCUSDLONGS to BITFINEX:BTCUSDSHORTS as a measure of market sentiment and how that sentiment would magnify RSI changes. The volatility of the BTCUSDLONGS : BTCUSDSHORTS ratio was too low to get a good read, using a percent rank of the RSI of the ratio made the results more visible. After a discussion with @jason5480 I saw how opening it up to all margined Long / Short pairs was the best way forward. Unfortunately the name no longer matched the script, so I had to publish a new script.
RSI vs BITFINEX BTC Longs/Shorts Margin Ratio Percentage RankThis indicator plots the RSI of the current token with a color based on percentage rank of the RSI of BITFINEX:BTCUSDLONGS divided by BITFINEX:BTCUSDSHORTS, with a plot of the moving average of the RSI. It can optionally plot the RSI in white and the ratio RSI in color, or the ratio as background color. It can also plot the raw ratio rather than the percentage rank if selected.
I was interested in the ratio of BITFINEX:BTCUSDLONGS to BITFINEX:BTCUSDSHORTS as a measure of market sentiment and how that sentiment would magnify RSI changes. The volatility of the BTCUSDLONGS : BTCUSDSHORTS ratio was too low to get a good read, using a percent rank of the RSI of the ratio made the results more visible.
This indicator should be used on a BTC chart.
Trend Sentiment [racer8]Trend Sentiment is a trend indicator with enhanced graphics, that is, it has many different shades of blue and red.
The brighter the blue, the more bullish.
The brighter the red, the more bearish.
It is a simple indicator with a basic formula:
a = close > prev.close? ---> If yes, a = 1, otherwise a = 0.
b = sma of a over n periods -----1st parameter, n...."Length"
c = sma of b over j periods ----- 2nd parmeter, j..."Smoothing"
plot (c)
Is c > 0.5? ---> If yes, background color = blue, otherwise red.
plot background color.
plot 0.5 as dotted midline.
The Trend Sentiment value represents the percentage of bullish force in the market.
Signals are generated when it crosses the 50% mark.
Values above 0.50 are bullish and values below 0.50 are bearish.
Enjoy and hit the like button :)
Blockchain Fundamentals - Satoshies Per Dollar by Cryptorhythms🔗Blockchain Fundamentals - Satoshis Per Dollar by Cryptorhythms
Intro
SPD is a new metric I propose which can be used to determine general sentiment and help narrow down periods to DCA .
Description
In the most basic sense this indicator is simply showing you how many satoshies are equal to one US dollar . This can be a useful metric to keep stored in the back of your mind. It can also give you a new satoshi based perspective on bitcoin pricing.
I simply added an MA selection option to give a basic sentiment reading. You could also use the red areas as a modified DCA (i.e. only do dollar cost averaging when red zone is in effect.
The indicator is not really meant for buy/sell signaling but more as a reference
👍 We hope you enjoyed this indicator and find it useful! We post free crypto analysis, strategies and indicators regularly. This is our 71st script on Tradingview!
💬Check my Signature for other information
NY Anchored VWAP and Auto SMANY Anchored VWAP and Auto SMA
This script is a versatile trading indicator for the TradingView platform that combines two powerful components: a New York-anchored Volume-Weighted Average Price (VWAP) and a dynamic Simple Moving Average (SMA). Designed for traders who utilize VWAP for intraday trend analysis, this tool provides a clear visual representation of average price and volatility-adjusted moving averages, generating automated alerts for key crossover signals.
Indicator Components
1. NY Anchored VWAP
The VWAP is a crucial tool that represents the average price of a security adjusted for volume. This version is "anchored" to the start of the New York trading session, resetting at the beginning of each new session. This provides a clean, session-specific anchor point to gauge market sentiment and trend. The VWAP line changes color to reflect its slope:
Green: When the VWAP is trending upwards, indicating a bullish bias.
Red: When the VWAP is trending downwards, indicating a bearish bias.
2. Auto SMA
The Auto SMA is a moving average with a unique twist: its lookback period is not fixed. Instead, it dynamically adjusts based on market volatility. The script measures volatility using the Average True Range (ATR) and a Z-Score calculation.
When volatility is expanding, the SMA's length shortens, making it more sensitive to recent price changes.
When volatility is contracting, the SMA's length lengthens, smoothing out the price action to filter out noise.
This adaptive approach allows the SMA to react appropriately to different market conditions.
Suggested Trading Strategy
This indicator is particularly effective when used on a one-minute chart for identifying high-probability trade entries. The core of the strategy is to trade the crossover between the VWAP and the Auto SMA, with confirmation from a candle close.
The strategy works best when the entry signal aligns with the overall bias of the higher timeframe market structure. For example, if the daily or 4-hour chart is in an uptrend, you would look for bullish signals on the one-minute chart.
Bullish Entry Signal: A potential entry is signaled when the VWAP crosses above the Auto SMA, and is confirmed when the one-minute candle closes above both the VWAP and the SMA. This indicates a potential continuation of the bullish momentum.
Bearish Entry Signal: A potential entry is signaled when the VWAP crosses below the Auto SMA, and is confirmed when the one-minute candle closes below both the VWAP and the SMA. This indicates a potential continuation of the bearish momentum.
The built-in alerts for these crossovers allow you to receive notifications without having to constantly monitor the charts, ensuring you don't miss a potential setup.
Fear & Greed Oscillator — LEAPs (v6, manual DMI/ADX)Fear & Greed Oscillator for LEAPs — a composite sentiment/trend tool that highlights long-term fear/greed extremes and trend quality for better LEAP entries and exits.
This custom Fear & Greed Oscillator (FGO-LEAP) is designed for swing trades and long-term LEAP option entries. It blends multiple signals — MACD (trend), ADX/DMI (trend quality), OBV (accumulation/distribution), RSI & Stoch RSI (momentum), and volume spikes — into a single score that ranges from –100 (extreme fear) to +100 (extreme greed). The weights are tuned for LEAPs, emphasizing slower trend and accumulation signals rather than short-term noise.
Use Weekly charts for the main signal and Daily only for entry timing. Entries are strongest when the score is above zero and rising, with both MACD and DMI positive. Extreme Fear (< –60) can mark long-term bottoms when followed by a recovery, while Extreme Greed (> +60) often signals overheated conditions. A cross below zero is an early warning to reduce or roll positions.
