XRP Comparative RSI Indicator - Final VersionXRP Comparative RSI Indicator - Final Version
The XRP Comparative RSI Indicator offers a dynamic analysis of XRP’s market positioning through relative strength index (RSI) comparisons across various cryptocurrencies and major market indicators. This indicator allows traders and analysts to gauge XRP’s momentum and potential turning points within different market conditions.
Key Features:
• Normalized RSIs: Each RSI value is normalized between 0.00 and 1.00, allowing seamless comparison across multiple assets.
• Grouped Analysis: Three RSI groups provide specific insights:
• Group 1 (XRP-Specific): Measures XRPUSD, XRP Dominance (XRP.D), and XRP/BTC, focusing on XRP’s performance across different trading pairs.
• Group 2 (Market Influence - Bitcoin): Measures BTCUSD, BTC Dominance (BTC.D), and XRP/BTC, capturing the influence of Bitcoin on XRP.
• Group 3 (Liquidity Impact): Measures USDT Dominance (USDT.D), BTCUSD, and ETHUSD, evaluating the liquidity impact from key assets and stablecoins.
• Individual Asset RSIs: Track the normalized RSI for each specific pair or asset, including XRPUSD, BTCUSD, ETHUSD, XRP/BTC, BTC Dominance, ETH Dominance, and the S&P 500.
• Clear Color Coding: Each asset’s RSI is plotted with a unique color scheme, consistent with the first indicator, for easy recognition.
This indicator is ideal for identifying relative strengths, potential entry and exit signals, and understanding how XRP’s momentum aligns or diverges from broader market trends.
在脚本中搜索"liquidity"
Rounded Grid Levels🟩 Rounded Grid Levels is a visual tool that helps traders quickly identify key psychological price levels on any chart. By dynamically adapting to the user's visible screen area, it provides consistent, easy-to-read round number grids that align with price action. The indicator offers a traditional visualization of horizontal round level grids, along with enhanced options such as tilted grids that align with market sentiment, and fan-shaped grids for alternative price interaction views. It serves purely as a visual aid, providing an adaptable way to observe rounded price levels without making predictions or generating trading signals.
⚡ OVERVIEW ⚡
The Rounded Grid Levels indicator is a visual tool designed to help traders identify and track price levels that may hold psychological significance, such as round numbers or significant milestones. These levels often serve as potential areas for price reactions, including support, resistance, or points of market interest. The indicator's gridlines are determined by user-defined settings and adjust dynamically based on the visible chart area, meaning they are influenced by the user's current zoom level and perspective. This behavior is similar to TradingView's built-in grid lines found in the chart settings canvas, which also adjust in real-time based on the visible screen, ensuring the most relevant price levels are displayed. By default, the indicator provides consistent gridlines to represent traditional round number levels, offering a straightforward view of key psychological areas. Additionally, users have access to experimental and novel configurations, such as fan-shaped layouts, which expand from a central point and adapt directionally based on user settings. This configuration can provide an alternate perspective for traders, especially useful in analyzing broader market moves and visualizing expansion relative to the current price.
Users can display the gridlines in a variety of configurations, including horizontal, neutral, auto, or fan-shaped layouts, depending on their preferred method of analysis. This flexibility allows traders to focus on different types of price action without overcrowding the visual representation of price movements.
This indicator is intended purely as a visual aid for understanding how price interacts with rounded levels over time. It does not generate predictive trading signals or recommendations but rather provides traders with a customizable framework to enhance their market analysis.
⭕ ROUND NUMBERS IN MARKET PSYCHOLOGY ⭕
Round numbers hold a significant place in financial markets, largely due to the psychological tendencies of traders and investors. These levels often represent areas of interest where human behavior, market biases, and trading strategies converge. Whether it's prices ending in 000, 500, or other recognizable values, these levels naturally attract more attention and influence decision-making.
Round numbers can act as key support or resistance levels and often become focal points in market activity. They are frequently highlighted by financial media, embedded in products like options, and serve as foundations for various trading theories. Their impact extends across different market participants and strategies, making them important focal points in both short-term and long-term market analysis.
Round numbers play an important role in guiding trader behavior and market activity. To better understand why these levels are so impactful, there are several key factors that highlight their significance in trading and price dynamics:
Psychological Impact : Humans naturally gravitate toward round numbers, such as prices ending in 000, 500, or 00. These levels tend to draw attention as traders perceive them as psychologically significant. This behavior is rooted in the cognitive bias known as "left-digit bias," where people assign greater importance to rounded, more recognizable numbers. In trading, this means that prices at these levels are more memorable and thus more likely to attract attention, creating an area where traders focus their buying or selling decisions.
Order Clustering : Traders often place buy and sell orders around these rounded levels, either manually or automatically through stop and limit orders. This clustering leads to the formation of visible support or resistance zones, as the concentrated orders tend to influence price behavior around these key levels. Market participants tend to converge their orders around these price points because of their perceived psychological importance, creating a liquidity pocket. As a result, these areas often act as barriers that the price either struggles to cross or uses as springboards for further movement.
External Influences : Financial media frequently highlights round-number milestones, amplifying market sentiment and drawing traders' attention to these levels. Additionally, algorithmic trading systems often react to round-number thresholds, which can further reinforce price movements, creating self-reinforcing reactions at these levels. As media and analysts emphasize these milestones, more traders pay attention to them, leading to increased volume and often heightened volatility at those points. This self-reinforcing cycle makes round numbers an area where price movement can either accelerate due to a breakout or stall because of clustering interest.
Option Strike Prices : Options contracts typically have strike prices set at round numbers, and as expiration approaches, these levels can influence the price of the underlying asset due to concentrated trading activity. The behavior around these levels, often called "pinning," happens because traders adjust their positions to avoid unfavorable scenarios at these key strikes. This activity tends to concentrate price movement toward these levels as traders hedge their positions, leading to increased liquidity and the potential for abrupt price reactions near option expiration dates.
Whole Number Theory : This theory suggests that whole numbers act as natural psychological barriers, where traders tend to make decisions, place orders, or expect price reactions, making these levels crucial for analysis. Whole numbers are simple to remember and are often used as informal targets for profit-taking or stop placement. This behavior leads to a natural ebb and flow around these levels, where the market finds equilibrium temporarily before deciding on a future direction. Whole numbers tend to work like magnets, drawing price to them and often creating reactions that are visible across different timeframes.
Quarters Theory : Commonly used in Forex markets, this theory focuses on quarter-point increments (e.g., 1.0000, 1.2500, 1.5000) as key levels where price often pauses or reverses. These quarter levels are treated as important psychological barriers, with price frequently interacting at these intervals. Traders use these points to gauge market strength or weakness because quarter levels divide larger round-number ranges into more manageable and meaningful segments. For example, in highly traded forex pairs like EUR/USD, traders might treat 1.2500 as a significant barrier because it represents a halfway point between 1.0000 and 1.5000, offering a balanced reference point for decision-making.
Big Round Numbers : Major round numbers, such as 100, 500, or 1000, often attract significant attention and serve as psychological thresholds. Traders anticipate strong reactions when prices approach or cross these levels. This is often because large round numbers symbolize major milestones, and price behavior around them tends to signal important market sentiment shifts. When price crosses a major level, such as a stock moving above $100 or Bitcoin crossing $50,000, it often creates a surge in trading activity as it is viewed as a validation or invalidation of market trends, drawing in momentum traders and triggering both retail and institutional responses.
By visualizing these round levels on the chart, the Rounded Grid Levels indicator helps traders identify areas where price may pause, reverse, or gain momentum. While round numbers provide useful insights, they should be used in conjunction with other technical analysis tools for a comprehensive trading strategy.
🛠️ CONFIGURATION AND SETTINGS 🛠️
The Rounded Grid Levels indicator offers a variety of configurable settings to tailor the visualization according to individual trader preferences. Below are the key settings available for customization:
Custom Settings
Rounding Step : The Rounding Step parameter sets the minimum interval between gridlines. This value determines how closely spaced the rounded levels are on the chart. For example, if the Rounding Step is set to 100, gridlines will be displayed at every 100 points (e.g., $100, $200, $300) relative to the current price level. The Rounding Step is scaled to the chart's visible area, meaning users should adjust it appropriately for different assets to ensure effective visualization. Lower values provide a more granular view, while larger values give a broader, higher-level perspective.
Major Grids : Defines the interval at which major gridlines will appear compared to minor ones. For example, if the Rounding Step is 100 and Major Grids is set to 10, major gridlines will be displayed every $1,000, while minor gridlines will be at every $100. This distinction allows traders to better visualize key psychological levels by emphasizing significant price intervals.
Direction : Users can select the gridline direction, choosing between options such as 'Up', 'Down', 'Auto', or 'Neutral'. This setting controls how the gridlines extend relative to the current price level, which can help in analyzing directional trends.
Neutral Direction : This option provides balanced gridlines both above and below the current price, allowing traders to visualize support and resistance levels symmetrically. This is useful for analyzing sideways or ranging markets without directional bias.
Up Direction : The gridlines are tilted upwards, starting from visible lows and extending toward the rounded level at the current price. By choosing Up , traders emphasize an upward sentiment, visualizing price action that aligns with rising trends. This option helps illustrate potential areas where pullbacks may occur, as well as how price might expand upwards in the current market context.
Down Direction : The gridlines are tilted downwards, starting from visible highs and extending toward the rounded level at the current price. Selecting Down allows traders to emphasize a downward sentiment, visualizing how price may expand downwards, which is particularly useful when analyzing downtrends or potential correction levels. The gridlines provide an illustrative view of how price interacts with lower levels during market declines.
Auto Direction : The gridlines automatically adjust their direction based on recent market trends. This adaptive option allows traders to visualize gridlines that dynamically change according to price action, making it suitable for evolving market conditions where the direction is uncertain. It’s useful for traders looking for an indicator that moves in sync with market shifts and doesn’t require manual adjustment.
Grid Type : Allows users to choose between 'Linear' or 'Fan' grid types. The Linear type creates evenly spaced gridlines that can be either horizontal or tilted, depending on the chosen direction setting, providing a straightforward view of price levels. The Fan type radiates lines from a central point, offering a more dynamic perspective for analyzing price expansions relative to the current price. These grid types introduce experimental visualizations influenced by chart properties, including visible highs, lows, and the current price. Regardless of the configuration, the gridlines will always end at the current bar, which represents a rounded price level, ensuring consistency in how key price areas are displayed.
Extend : This setting allows gridlines to be projected into the future, helping traders see potential levels beyond the current bar. When enabled, the behavior of the extended lines varies based on the selected grid type and direction. For Neutral and Horizontal Linear settings, the extended gridlines maintain their round-number alignment indefinitely. However, for Up , Down , or Auto directions, the angle of the extended gridlines can change dynamically based on the chart’s visible high and low or the latest price action. As a result, extended lines may not continue to align with round-number levels beyond the current bar, reflecting instead the current trend and sentiment of the market. Regardless of direction, extended gridlines remain consistently spaced and either parallel or evenly distributed, ensuring a structured visual representation.
Color Settings : Users can customize the colors for resistance, support, and minor gridlines at the current price. This helps in visually distinguishing between different grid types and their significance on the chart.
Color Options
These configuration options make the Rounded Grid Levels indicator a versatile tool for traders looking to customize their charts based on their personal trading strategies and analytical preferences.
🖼️ CHART EXAMPLES 🖼️
The following chart examples illustrate different configurations available in the Rounded Grid Levels indicator. These examples show how variations in grid type, direction, and rounding step settings impact the visualization of price levels. Traders may find that smaller rounding steps are more effective on lower time frames, where precision is key, whereas larger rounding steps help to reduce clutter and highlight key levels on higher time frames. Each image includes a caption to explain the specific configuration used, helping users better understand how to apply these settings in different market conditions.
Smaller Rounding Step (100) : With a smaller rounding step, the gridlines are spaced closely together. This setting is particularly useful for lower time frames where price action is more granular and finer details are needed. It allows traders to track price interactions at narrower levels, but on higher time frames, it may lead to clutter and exceed Pine Script's 500-line limit.
Larger Rounding Step (1000) : With a larger rounding step, the gridlines are spaced farther apart. This visualization is better suited for higher time frames or broader market overviews, allowing users to focus on major psychological levels without overloading the chart. On lower time frames, this may result in fewer actionable levels, but it helps in maintaining clarity and staying within Pine Script's line limit.
Linear Grid Type, Neutral Direction (Traditional Rounded Price Levels) : The Linear gridlines are displayed in a neutral fashion, representing traditional round-number levels with consistent spacing above and below the current price. This layout helps visualize key psychological price levels over time in a straightforward manner.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, remaining parallel and ending at the rounded level at the current price. This setup emphasizes downward market sentiment, allowing traders to visualize price expansion towards lower levels, which is useful when analyzing downtrends or potential correction levels.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, extending from the current price to lower levels. Useful for observing downtrending price movements and visualizing pullback areas during uptrends.
Linear Grid Type, Auto Direction : The Linear gridlines adjust dynamically, tilting either upwards or downwards to align with recent price trends, remaining parallel and ending at the rounded level at the current price. This configuration reflects the current market sentiment and offers traders a flexible way to observe price dynamics as they develop in real time.
Fan Grid Type, Neutral Direction : The fan-shaped gridlines radiate symmetrically from a central point, ending at the rounded level at the current price. This configuration provides an unbiased view of price action, giving traders a balanced visualization of rounded levels without directional influence.
Fan Grid Type, Up Direction : The fan-shaped gridlines originate from lower visible price points and radiate upwards, ending at the rounded level at the current price. This layout helps visualize potential price expansion to higher levels, offering insights into upward momentum while maintaining a dynamic and evolving perspective on market conditions.
Fan Grid Type, Down Direction : The fan-shaped gridlines originate from higher visible price points and radiate downwards, ending at the rounded level at the current price. This setup is particularly useful for observing potential price expansion towards lower levels, illustrating areas where the price might extend during a downtrend.
Fan Grid Type, Auto Direction : The fan-shaped gridlines dynamically adjust, originating from visible chart points based on the current market trend, and radiate outward, ending at the rounded level at the current price. This adaptive visualization offers a continuously evolving representation that aligns with changing market sentiment, helping traders assess price expansion dynamically.
📊 SUMMARY 📊
The Rounded Grid Levels indicator helps traders highlight important round-number price levels on their charts, providing a dynamic way to visualize these psychological areas. With customizable gridline options—including traditional, tilted, and fan-shaped styles—users can adapt the indicator to suit their analysis needs. The gridlines adjust with chart zoom or scale, offering a flexible tool for observing price action, without providing specific trading signals or predictions.
⚙️ COMPATIBILITY AND LIMITATIONS ⚙️
Asset Compatibility :
The Rounded Grid Levels indicator is compatible with all asset classes, including cryptocurrencies, forex, stocks, and commodities. Users should adjust both the Rounding Step and the Major Grid settings to ensure the correct scale is used for the specific asset. This adjustment ensures that the most relevant round price levels are displayed effectively regardless of the instrument being analyzed. For instance, when analyzing BTCUSD, a higher Rounding Step may be needed compared to forex pairs like EURUSD, and the Major Grid value should also be adjusted to appropriately emphasize significant levels.
Line Limitations in Pine Script :
The Rounded Grid Levels indicator is subject to Pine Script's 500-line limit. This means that it cannot draw more than 500 gridlines on the chart at any given time. The number of gridlines depends directly on the chosen Rounding Step . If the steps are too small, the gridlines will be spaced too closely, causing the indicator to quickly reach the line limit. For example, if Ethereum is trading around $2,500, a Rounding Step of 100 might be appropriate, but a step of 1.00 would create too many gridlines, exceeding Pine Script's limit. Users should consider appropriate settings to avoid running into this constraint.
Runtime Error Considerations
When using the Rounded Grid Levels indicator, users might encounter a runtime error in specific scenarios. This typically happens if the Rounding Step is set too small, causing the indicator to exceed Pine Script's line limit or take too long to process. This can often occur when switching between charts that have significantly different price ranges. Since the Rounding Step requires flexibility to work with a wide variety of assets—ranging from decimals to thousands—it is not practically limited within the script itself. If a runtime error occurs, the recommended solution is to increase the Rounding Step to a larger value that better matches the current asset's price range.
Runtime Error: If the Rounding Step is too small for the current asset or chart, the indicator may generate a runtime error. Users should increase the Rounding Step to ensure proper visualization.
⚠️ DISCLAIMER ⚠️
The Rounded Grid Levels indicator is not designed as a predictive tool. While it extends gridlines into the future, this extension is purely for visual continuity and does not imply any forecast of future price movements. The primary function of this indicator is to help users visualize significant round number price levels.
The gridlines adjust dynamically based on the visible chart range, ensuring that the most relevant round price levels are displayed. This behavior allows the indicator to adapt to your current view of the market, but it should not be used to predict price movements. The indicator is intended as a visual aid and should be used alongside other tools in a comprehensive market analysis approach.
While gridlines may align with significant price levels in hindsight, they should not be interpreted as indicators of future price movements. Traders are encouraged to adjust settings based on their strategy and market conditions.
🧠 BEYOND THE CODE 🧠
The Rounded Grid Levels indicator, like other xxattaxx indicators , is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new grid calculation indicators, drawings, and strategies. We hope this indicator serves as a framework and a starting point for future innovations in grid trading.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We actively encourage your feedback and contributions, which will directly help us refine and improve the Rounded Grid Levels indicator. We look forward to seeing the creative ways in which you use and enhance this tool.
Advanced Multi-Seasonality StrategyThe Multi-Seasonality Strategy is a trading system based on seasonal market patterns. Seasonality refers to recurring market trends driven by predictable calendar-based events. These patterns emerge due to economic cycles, corporate activities (e.g., earnings reports), and investor behavior around specific times of the year. Studies have shown that such effects can influence asset prices over defined periods, leading to opportunities for traders who exploit these patterns (Hirshleifer, 2001; Bouman & Jacobsen, 2002).
How the Strategy Works:
The strategy allows the user to define four distinct periods within a calendar year. For each period, the trader selects:
Entry Date (Month and Day): The date to enter the trade.
Holding Period: The number of trading days to remain in the trade after the entry.
Trade Direction: Whether to take a long or short position during that period.
The system is designed with flexibility, enabling the user to activate or deactivate each of the four periods. The idea is to take advantage of seasonal patterns, such as buying during historically strong periods and selling during weaker ones. A well-known example is the "Sell in May and Go Away" phenomenon, which suggests that stock returns are higher from November to April and weaker from May to October (Bouman & Jacobsen, 2002).
Seasonality in Financial Markets:
Seasonal effects have been documented across different asset classes and markets:
Equities: Stock markets tend to exhibit higher returns during certain months, such as the "January effect," where prices rise after year-end tax-loss selling (Haugen & Lakonishok, 1987).
Commodities: Agricultural commodities often follow seasonal planting and harvesting cycles, which impact supply and demand patterns (Fama & French, 1987).
Forex: Currency pairs may show strength or weakness during specific quarters based on macroeconomic factors, such as fiscal year-end flows or central bank policy decisions.
Scientific Basis:
Research shows that market anomalies like seasonality are linked to behavioral biases and institutional practices. For example, investors may respond to tax incentives at the end of the year, and companies may engage in window dressing (Haugen & Lakonishok, 1987). Additionally, macroeconomic factors, such as monetary policy shifts and holiday trading volumes, can also contribute to predictable seasonal trends (Bouman & Jacobsen, 2002).
Risks of Seasonal Trading:
While the strategy seeks to exploit predictable patterns, there are inherent risks:
Market Changes: Seasonal effects observed in the past may weaken or disappear as market conditions evolve. Increased algorithmic trading, globalization, and policy changes can reduce the reliability of historical patterns (Lo, 2004).
Overfitting: One of the risks in seasonal trading is overfitting the strategy to historical data. A pattern that worked in the past may not necessarily work in the future, especially if it was based on random chance or external factors that no longer apply (Sullivan, Timmermann, & White, 1999).
Liquidity and Volatility: Trading during specific periods may expose the trader to low liquidity, especially around holidays or earnings seasons, leading to slippage and larger-than-expected price swings.
Economic and Geopolitical Shocks: External events such as pandemics, wars, or political instability can disrupt seasonal patterns, leading to unexpected market behavior.
Conclusion:
The Multi-Seasonality Strategy capitalizes on the predictable nature of certain calendar-based patterns in financial markets. By entering and exiting trades based on well-established seasonal effects, traders can potentially capture short-term profits. However, caution is necessary, as market dynamics can change, and seasonal patterns are not guaranteed to persist. Rigorous backtesting, combined with risk management practices, is essential to successfully implementing this strategy.
References:
Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, "Sell in May and Go Away": Another Puzzle. American Economic Review, 92(5), 1618-1635.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage. Journal of Business, 60(1), 55-73.
Haugen, R. A., & Lakonishok, J. (1987). The Incredible January Effect: The Stock Market's Unsolved Mystery. Dow Jones-Irwin.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance, 56(4), 1533-1597.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance, 54(5), 1647-1691.
This strategy harnesses the power of seasonality but requires careful consideration of the risks and potential changes in market behavior over time.
asia session w shieldIntroduction
This Script displays the Asia Session Range
Description
The Indicator is based on UTC -7 timing but displays the Session Boxes automatically correct at your chart so you do not have to adjust any timings based on your Time Zone and don't have to do any calculations based on your UTC. It is already perfect.
You will see on default settings the blue Asia Box, the special ' invalid shield ' feature is there because first two hours are spread timing.
Most Timing-based Indicators have "bugged" boxes or don't show clean boxes at all and don't adjust at daylight savings times, we made sure that everything automatically gets adjusted so you don't have to! So the timings will always display at the correct time regarding the daylight savings times.
Combining Timing with Liquidity Zones the right way and in a clear, clean, and simple format.
Different than others this script also shows the "true" Asia range as it respects the "day open gap" which affects the Asia range in other scripts and it also covers the full 8 hours of Asia Session.
Recommended Use
The most beautiful display is on the M5 Timeframe as you have a clear overview of all sessions without losing the intraday view. You can also use it on the M1 for more details or the M15 for the bigger picture. The Template can hide on higher time frames starting from the H1 to not flood your chart with boxes.
How to use the Asia Session Range Box
Use the Asia Range Box as your intraday Guide, keep in mind that a Breakout of Asia high or low induces Liquidity and a common price behavior is a reversal after the fake breakout of that range.
Connors VIX Reversal III invented by Dave LandryThis strategy is based on trading signals derived from the behavior of the Volatility Index (VIX) relative to its 10-day moving average. The rules are split into buying and selling conditions:
Buy Conditions:
The VIX low must be above its 10-day moving average.
The VIX must close at least 10% above its 10-day moving average.
If both conditions are met, a buy signal is generated at the market's close.
Sell Conditions:
The VIX high must be below its 10-day moving average.
The VIX must close at least 10% below its 10-day moving average.
If both conditions are met, a sell signal is generated at the market's close.
Exit Conditions:
For long positions, the strategy exits when the VIX trades intraday below its previous day’s 10-day moving average.
For short positions, the strategy exits when the VIX trades intraday above its previous day’s 10-day moving average.
This strategy is primarily a mean-reversion strategy, where the market is expected to revert to a more normal state after the VIX exhibits extreme behavior (i.e., large deviations from its moving average).
About Dave Landry
Dave Landry is a well-known figure in the world of trading, particularly in technical analysis. He is an author, trader, and educator, best known for his work on swing trading strategies. Landry focuses on trend-following and momentum-based techniques, teaching traders how to capitalize on shorter-term price swings in the market. He has written books like "Dave Landry on Swing Trading" and "The Layman's Guide to Trading Stocks," which emphasize practical, actionable trading strategies.
About Connors Research
Connors Research is a financial research firm known for its quantitative research in financial markets. Founded by Larry Connors, the firm specializes in developing high-probability trading systems based on historical market behavior. Connors’ work is widely respected for its data-driven approach, including systems like the RSI(2) strategy, which focuses on short-term mean reversion. The firm also provides trading education and tools for institutional and retail traders alike, emphasizing strategies that can be backtested and quantified.
Risks of the Strategy
While this strategy may appear to offer promising opportunities to exploit extreme VIX movements, it carries several risks:
Market Volatility: The VIX itself is a measure of market volatility, meaning the strategy can be exposed to sudden and unpredictable market swings. This can result in whipsaws, where positions are opened and closed in rapid succession due to sharp reversals in the VIX.
Overfitting: Strategies based on specific conditions like the VIX closing 10% above or below its moving average can be subject to overfitting, meaning they work well in historical tests but may underperform in live markets. This is a common issue in quantitative trading systems that are not adaptable to changing market conditions .
Mean-Reversion Assumption: The core assumption behind this strategy is that markets will revert to their mean after extreme movements. However, during periods of sustained trends (e.g., market crashes or rallies), this assumption may break down, leading to prolonged drawdowns.
Liquidity and Slippage: Depending on the asset being traded (e.g., S&P 500 futures, ETFs), liquidity issues or slippage could occur when executing trades at market close, particularly in volatile conditions. This could increase costs or worsen trade execution.
Scientific Explanation of the Strategy
The VIX is often referred to as the "fear gauge" because it measures the market's expectations of volatility based on options prices. Research has shown that the VIX tends to spike during periods of market stress and revert to lower levels when conditions stabilize . Mean reversion strategies like this one assume that extreme VIX levels are unsustainable in the long run, which aligns with findings from academic literature on volatility and market behavior.
Studies have found that the VIX is inversely correlated with stock market returns, meaning that higher VIX levels often correspond to lower stock prices and vice versa . By using the VIX’s relationship with its 10-day moving average, this strategy aims to capture reversals in market sentiment. The 10% threshold is designed to identify moments when the VIX is significantly deviating from its norm, signaling a potential reversal.
However, academic research also highlights the limitations of relying on the VIX alone for trading signals. The VIX does not predict market direction, only volatility, meaning that it cannot indicate the magnitude of price movements . Furthermore, extreme VIX levels can persist longer than expected, particularly during financial crises.
In conclusion, while the strategy is grounded in well-established financial principles (e.g., mean reversion and the relationship between volatility and market performance), it carries inherent risks and should be used with caution. Backtesting and careful risk management are essential before applying this strategy in live markets.
TRIN (Arms Index) Trading StrategyThe TRIN (Arms Index), also known as the Short-Term Trading Index, is a technical indicator designed to gauge the internal strength or weakness of the market. It compares the number of advancing and declining stocks to the advancing and declining volume (AD Volume). A TRIN value above 1.0 generally indicates bearish market conditions, while a value below 1.0 suggests bullish market sentiment.
Strategy Rules:
Entry Condition (Long Position): When the TRIN value is above 1.0, the strategy enters a long position, indicating that the market may be oversold, and a potential reversal could occur.
Exit Condition: The strategy exits the long position when the closing price is higher than the previous day’s high, signaling a potential rebound in the market.
This strategy aims to capitalize on short-term market inefficiencies by entering trades during periods of potential market weakness and exiting when signs of recovery appear.
How the TRIN Index Works:
The TRIN is calculated as follows:
TRIN=Advancing Issues / Declining IssuesAdvancing Volume / Declining Volume
TRIN=Advancing Volume / Declining VolumeAdvancing Issues / Declining Issues
A TRIN value above 1.0 indicates that the market is potentially oversold (more declining stocks with higher volume), while a value below 1.0 suggests the market may be overbought (more advancing stocks with higher volume) .
Empirical Evidence:
Market Sentiment Indicator: The TRIN has been widely used as a sentiment indicator. Research by Zweig (1997) suggests that extreme TRIN values can serve as a contrarian signal, indicating potential turning points in the market. For instance, a TRIN above 2.0 is often considered a sign of panic selling, which can precede a market bottom .
Overbought/Oversold Conditions: Studies have shown that indicators like TRIN, which measure market breadth and volume, can be effective in identifying overbought and oversold conditions. According to Fama and French (1988), market sentiment indicators that consider both price and volume data can offer insights into future price movements .
Risks and Limitations:
False Signals:
One of the primary risks of using the TRIN-based strategy is the possibility of false signals. A TRIN value above 1.0 does not always guarantee a market rebound, especially in sustained bearish trends. In such cases, the strategy might enter long positions prematurely, leading to losses.
Research by Brock, Lakonishok, and LeBaron (1992) found that while market indicators like TRIN can be useful, they are not foolproof and can generate multiple false positives, particularly in volatile markets .
Market Regimes:
The effectiveness of the TRIN index can vary depending on the market regime. In strongly trending markets, either bullish or bearish, the TRIN may not provide reliable reversal signals, and relying on it could result in trades that go against the prevailing trend. For instance, during strong bear markets, the TRIN may frequently remain above 1.0, leading to multiple losing trades as the market continues to decline.
Short-Term Focus:
The TRIN strategy is inherently short-term focused, aiming to capture quick market reversals. This makes it sensitive to market noise and less effective for longer-term investors. Moreover, short-term trading strategies often require more frequent adjustments and can incur higher transaction costs, which may erode profitability over time.
Liquidity and Execution Risk:
Since the TRIN strategy requires entering and exiting trades based on short-term market movements, it is vulnerable to liquidity and execution risks. In fast-moving markets, the execution of trades may be delayed, leading to slippage and potentially unfavorable entry or exit points.
Conclusion:
The TRIN (Arms Index) Trading Strategy can be an effective tool for traders looking to capitalize on short-term market inefficiencies and potential reversals. However, it is important to recognize the risks associated with this strategy, including false signals, sensitivity to market regimes, and execution risks. Traders should employ proper risk management techniques and consider combining the TRIN with other indicators to improve the robustness of the strategy.
While the TRIN provides valuable insights into market sentiment, it is not a standalone solution and should be used in conjunction with a broader trading plan that takes into account both technical and fundamental analysis.
References:
Arms, Richard W. "Volume Adjusted Moving Averages." Technical Analysis of Stocks & Commodities, 1993.
Zweig, Martin. Winning on Wall Street. Warner Books, 1997.
Fama, Eugene F., and Kenneth R. French. "Permanent and Temporary Components of Stock Prices." Journal of Political Economy, 1988.
Brock, William, Josef Lakonishok, and Blake LeBaron. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 1992.
Swing Failure Pattern SFP [TradingFinder] SFP ICT Strategy🔵 Introduction
The Swing Failure Pattern (SFP), also referred to as a "Fake Breakout" or "False Breakout," is a vital concept in technical analysis. This pattern is derived from classic technical analysis, price action strategies, ICT concepts, and Smart Money Concepts.
It’s frequently utilized by traders to identify potential trend reversals in financial markets, especially in volatile markets like cryptocurrencies and forex. SFP helps traders recognize failed attempts to breach key support or resistance levels, providing strategic opportunities for trades.
The Swing Failure Pattern (SFP) is a popular strategy among traders used to identify false breakouts and potential trend reversals in the market. This strategy involves spotting moments where the price attempts to break above or below a previous high or low (breakout) but fails to sustain the move, leading to a sharp reversal.
Traders use this strategy to identify liquidity zones where stop orders (stop hunt) are typically placed and targeted by larger market participants or whales.
When the price penetrates these areas but fails to hold the levels, a liquidity sweep occurs, signaling exhaustion in the trend and a potential reversal. This strategy allows traders to enter the market at the right time and capitalize on opportunities created by false breakouts.
🟣 Types of SFP
When analyzing SFPs, two main variations are essential :
Real SFP : This occurs when the price breaks a critical level but fails to close above it, then quickly reverses. Due to its clarity and strong signal, this SFP type is highly reliable for traders.
Considerable SFP : In this scenario, the price closes slightly above a key level but quickly declines. Although significant, it is not as definitive or trustworthy as a Real SFP.
🟣 Understanding SFP
The Swing Failure Pattern, or False Breakout, is identified when the price momentarily breaks a crucial support or resistance level but cannot maintain the movement, leading to a rapid reversal.
The pattern can be categorized as follows :
Bullish SFP : This type occurs when the price dips below a support level but rebounds above it, signaling that sellers failed to push the price lower, indicating a potential upward trend.
Bearish SFP : This pattern forms when the price surpasses a resistance level but fails to hold, suggesting that buyers couldn’t maintain the higher price, leading to a potential decline.
🔵 How to Use
To effectively identify an SFP or Fake Breakout on a price chart, traders should follow these steps :
Identify Key Levels: Locate significant support or resistance levels on the chart.
Observe the Fake Breakout: The price should break the identified level but fail to close beyond it.
Monitor Price Reversal: After the breakout, the price should quickly reverse direction.
Execute the Trade: Traders typically enter the market after confirming the SFP.
🟣 Examples
Bullish Example : Bitcoin breaks below a $30,000 support level, drops to $29,000, but closes above $30,000 by the end of the day, signaling a Real Bullish SFP.
Bearish Example : Ethereum surpasses a $2,000 resistance level, rises to $2,100, but then falls back below $2,000, forming a Bearish SFP.
🟣 Pros and Cons of SFP
Pros :
Effective in identifying strong reversal points.
Offers a favorable risk-to-reward ratio.
Applicable across different timeframes.
Cons :
Requires experience and deep market understanding.
Risk of encountering false breakouts.
Should be combined with other technical tools for optimal effectiveness.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
SFP Type : Choose between "All", "Real" and "Considerable" modes to identify the swing failure pattern.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert SFP : Enables alerts for Swing Failure Pattern.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Swing Failure Pattern (SFP), or False Breakout, is an essential analytical tool that assists traders in identifying key market reversal points for successful trading.
By understanding the nuances between Real SFP and Considerable SFP, and integrating this pattern with other technical analysis tools, traders can make more informed decisions and better manage their trading risks.
ICT Intraday Timeline [neo.|]ICT Intraday Timeline is a script that aims to cleanly display key times that the "Inner Circle Trader" often refers to during the day on a separate pane in your Tradingview chart. While using it, you can clearly see the time it is currently in New York time, as well as your own through Tradingview as usual, as well as relevant times such as the lunch times, Silver Bullet times, and Asian range time.
By using this indicator it is simpler to consider what every time is doing and the effect it has on your current bias, for example: you may want to look at the 8:30 am open which is where news usually comes out, if not you can use 9:30 am for formulating trades. The AM SB is a time for when the "Silver Bullet (ICT)" setup can be found and executed, as it refines a specific range and targets inefficiencies and allows liquidity to form for which it comes back for, meaning it may be a better time for you to enter a trade, these are just examples of what you can look for, and how considering time can help you come up with and refine trade ideas.
Other times which are included are the:
Asia Range: You can mark out the highs and lows which occur during this time to use as liquidity later.
Midnight Open: On equities price will often interact with the midnight opening price, meaning it is an important time to consider.
London Open SB and Premarket SB: As mentioned previously you can find the "Silver Bullet" setup in here.
NY Lunch & London Lunch: Lunch times usually mean less volume therefore you may see less probable trades at this time.
AM SB and PM SB: Once again, times where you can potentially find more probable trades.
You can also easily customize any of the colors such as the SB (Silver Bullet) times, London lunch and NY Lunch times, or the Asia range or line colors to your preference and individual chart style.
ICT Balanced Price Range [TradingFinder] BPR | FVG + IFVG🔵 Introduction
The ICT Balanced Price Range (BPR) indicator is a valuable tool that helps traders identify key areas on price charts where a balance between buyers and sellers is established. These zones can serve as critical points for potential price reversals or continuations.
🟣 Bullish Balanced Price Range
A Bullish BPR forms when a buying pressure zone (Bullish FVG) overlaps with a Bullish Inversion FVG. This overlap indicates a high probability of price moving upwards, making it a crucial area for traders to consider.
🟣 Bearish Balanced Price Range
Similarly, a Bearish BPR is created when a selling pressure zone (Bearish FVG) overlaps with a Bearish Inversion FVG. This zone is often seen as a key area where the price is likely to move downward.
🔵 How to Use
🟣 Identifying the Balanced Price Range (BPR)
To identify the Balanced Price Range (BPR), you must first locate two Fair Value Gaps (FVGs) on the price chart. One FVG should be on the sell side, and the other on the buy side. When these two FVGs horizontally oppose each other, the area where they overlap is recognized as the Balanced Price Range (BPR).
This BPR zone is highly sensitive to price movements due to the combination of two FVGs, often leading to strong market reactions. As the price approaches this area, the likelihood of a significant market move increases, making it a prime target for professional traders.
🟣 Bullish Balanced Price Range (Bullish BPR)
To effectively trade using a Bullish BPR, begin by identifying a bullish market structure and searching for bullish Price Delivery Arrays (PD Arrays). Once the market structure shifts to bullish in a lower time frame, locate a Bullish FVG within the Discount Zone that overlaps with a Bearish FVG.
Mark this overlapping zone and wait for the price to test it before executing a buy trade. Alternatively, you can set a Buy Limit order with a stop loss below the recent swing low and target profits based on higher time frame liquidity draws.
🟣 Bearish Balanced Price Range (Bearish BPR)
For bearish trades, start by identifying a bearish market structure and look for bearish PD Arrays. After the market structure shifts to bearish in a lower time frame, identify a Bearish FVG within the Discount Zone that overlaps with a Bullish FVG. Mark this overlapping zone and execute a sell trade when the price tests it.
You can also use a Sell Limit order with a stop loss above the recent swing high and target profits according to higher time frame liquidity draws.
🔵 Settings
🟣 Global Settings
Show All Inversion FVG & IFVG : If disabled, only the most recent FVG & IFVG will be displayed.
FVG & IFVG Validity Period (Bar) : Determines the maximum duration (in number of candles) that the FVG and IFVG remain valid.
Switching Colors Theme Mode : Includes three modes: "Off", "Light", and "Dark". "Light" mode adjusts colors for light mode use, "Dark" mode adjusts colors for dark mode use, and "Off" disables color adjustments.
🟣 Display Settings
Show Bullish BPR : Toggles the display of demand-related boxes.
Show Bearish BPR : Toggles the display of supply-related boxes.
Mitigation Level BPR : Options include "Proximal", "Distal", or "50 % OB" modes, which you can choose based on your needs. The "50 % OB" line is the midpoint between distal and proximal.
Show Bullish IFVG : Toggles the display of demand-related boxes.
Show Bearish IFV G: Toggles the display of supply-related boxes.
Mitigation Level FVG and IFVG : Options include "Proximal", "Distal", or "50 % OB" modes, which you can choose based on your needs. The "50 % OB" line is the midpoint between distal and proximal.
🟣 Logic Settings
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter : Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter : Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter : Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filte r: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
🟣 Alert Settings
Alert Inversion FVG Mitigation : Enables alerts for Inversion FVG mitigation.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
Display More Info : Provides additional details in alert messages, including price range, date, hour, and minute. Set to 'Off' to exclude this information.
🔵 Conclusion
The ICT Balanced Price Range is a powerful and reliable tool for identifying key points on price charts. This strategy can be applied across various time frames and serves as a complementary tool alongside other indicators and technical analysis methods.
The most crucial aspect of utilizing this strategy effectively is correctly identifying FVGs and their overlapping areas, which comes with practice and experience.
Market Structure Based Stop LossMarket Structure Based Dynamic Stop Loss
Introduction
The Market Structure Based Stop Loss indicator is a strategic tool for traders designed to be useful in both rigorous backtesting and live testing, by providing an objective, “guess-free” stop loss level. This indicator dynamically plots suggested stop loss levels based on market structure, and the concepts of “interim lows/highs.”
It provides a robust framework for managing risk in both long and short positions. By leveraging historical price movements and real time market dynamics, this indicator helps traders identify quantitatively consistent risk levels while optimizing trade returns.
Legend
This indicator utilizes various inputs to customize its functionality, including "Stop Loss Sensitivity" and "Wick Depth," which dictate how closely the stop loss levels hug the price's highs and lows. The stop loss levels are plotted as lines on the trading chart, providing clear visual cues for position management. As seen in the chart below, this indicator dynamically plots stop loss levels for both long and short positions at every point in time.
A “Stop Loss Table” is also included, in order to enhance precision trading and increase backtesting accuracy. It is customizable in both size and positioning.
Case Study
Methodology
The methodology behind this indicator focuses on the precision placement of stop losses using market structure as a guide. It calculates stop losses by identifying the "lowest close" and the corresponding "lowest low" for long setups, and inversely for short setups. By adjusting the sensitivity settings, traders can tweak the indicator's responsiveness to price changes, ensuring that the stop losses are set with a balance between tight risk control and enough room to avoid premature exits due to market noise. The indicator's ability to adapt to different trading styles and time frames makes it an essential tool for traders aiming for efficiency and effectiveness in their risk management strategies.
An important point to make is the fact that the stop loss levels are always placed within the wicks. This is important to avoid what can be described as a “floating stop loss”. A stop loss placed outside of a wick is susceptible to an outsized degree of slippage. This is because traders always cluster their stop losses at high/low wicks, and a stop loss placed outside of this level will inevitably be caught in a low liquidity cascade or “wash-out.” When price approaches a cluster of stop losses, it is highly probable that you will be stopped out anyway, so it is prudent to attempt to be the trader who gets stopped out first in order to avoid high slippage, and losses above what you originally intended.
// For long positions: stop-loss is slightly inside the lowest wick
float dynamic_SL_Long = lowestClose - (lowestClose - lowestLow) * (1 - WickDepth)
// For short positions: stop-loss is slightly inside the highest wick
float dynamic_SL_Short = highestClose + (highestHigh - highestClose) * (1 - WickDepth)
The percentage depth of the wick in which the stop loss is placed is customisable with the “Wick Depth” variable, in order to customize stop loss strategies around the liquidity of the market a trader is executing their orders in.
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
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The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
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Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
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This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
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The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
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The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
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Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
High & Low Of Custom Session - Breakout True Open [cognyto]This indicator is based on the High & Low Of Custom Session - OpeningRange Breakout (Expo) created by Zeiierman.
It adds new functionality and enhances existing settings, targeting ES, NQ, and YM:
Manages session defaults to 12:00 to 13:00
New true opening fully customizable (default 13:00)
Manages timeframe visualization (default 15m and below)
Manages session draw length until the end of the current session (default NY)
Manages previous sessions, allowing the to be hidden
Improves timezone selection (default NY)
Following the strategy called Paradox detailed by DayTradingRauf, it works with indices like ES, NQ, and YM.
The rules consider three possible profiles:
First
AM session as consolidation (08:00-12:00)
Lunch hour range as consolidation (less than 100 points)
PM session breaking either side of the session range
Second
AM session trending lower (08:00-12:00)
Lunch hour range as consolidation (less than 100 points)
PM session trending higher
Third
AM session trending higher (08:00-12:00)
Lunch hour range as consolidation (less than 100 points)
PM session trending lower
After the session ends, the opening price at 13:00 is automatically drawn as it is a key point for the entry strategy.
The strategy can be monitored using a 5-minute or 15-minute timeframe as follows:
- Wait for a liquidity hunt (either the high or low of the lunch session range or AM is taken).
- If liquidity is taken, switch to the 1-minute timeframe and wait for a CISD (change in the state of delivery), where the price closes below an OB, or consider a breaker block or iFVG to enter the trade.
- Bullish entries should happen below the opening price at 13:00, and bearish entries should happen above.
- Consider a 1:2 reward ratio. However, runners can target the opposite side of the range that was not yet taken.
This indicator is for informational purposes only and you should not rely on any information it provides as legal, tax, investment, financial or other advice. Nothing provided by this indicator constitutes a solicitation, recommendation, endorsement or offer by cognyto or any third party service provider to buy or sell any securities or other financial instruments in this or any other jurisdiction in which such solicitation or offer would be unlawful under the securities laws of such jurisdiction.
US M2### Relevance and Functionality of the "US M2" Indicator
#### Relevance
The "US M2" indicator is relevant for several reasons:
1. **Macro-Economic Insight**: The M2 money supply is a critical indicator of the amount of liquidity in the economy. Changes in M2 can significantly impact financial markets, including equities, commodities, and cryptocurrencies.
2. **Trend Identification**: By analyzing the M2 money supply with moving averages, the indicator helps identify long-term and short-term trends, providing insights into economic conditions and potential market movements.
3. **Trading Signals**: The indicator generates bullish and bearish signals based on moving average crossovers and the difference between current M2 values and their moving averages. These signals can be useful for making informed trading decisions.
#### How It Works
1. **Data Input**:
- **US M2 Money Supply**: The indicator fetches the US M2 money supply data using the "USM2" symbol with a monthly resolution.
2. **Moving Averages**:
- **50-Period SMA**: Calculates the Simple Moving Average (SMA) over 50 periods (months) to capture short-term trends.
- **200-Period SMA**: Calculates the SMA over 200 periods to identify long-term trends.
3. **Difference Calculation**:
- **USM2 Difference**: Computes the difference between the current M2 value and its 50-period SMA to highlight deviations from the short-term trend.
4. **Amplification**:
- **Amplified Difference**: Multiplies the difference by 100 to make the deviations more visible on the chart.
5. **Bullish and Bearish Conditions**:
- **Bullish Condition**: When the current M2 value is above the 50-period SMA, indicating a positive short-term trend.
- **Bearish Condition**: When the current M2 value is below the 50-period SMA, indicating a negative short-term trend.
6. **Short-Term SMA of Amplified Difference**:
- **14-Period SMA**: Applies a 14-period SMA to the amplified difference to smooth out short-term fluctuations and provide a clearer trend signal.
7. **Plots and Visualizations**:
- **USM2 Plot**: Plots the US M2 data for reference.
- **200-Period SMA Plot**: Plots the long-term SMA to show the broader trend.
- **Amplified Difference Histogram**: Plots the amplified difference as a histogram with green bars for bullish conditions and red bars for bearish conditions.
- **SMA of Amplified Difference**: Plots the 14-period SMA of the amplified difference to track the trend of deviations.
8. **Moving Average Cross Signals**:
- **Bullish Cross**: Plots an upward triangle when the 50-period SMA crosses above the 200-period SMA, signaling a potential long-term uptrend.
- **Bearish Cross**: Plots a downward triangle when the 50-period SMA crosses below the 200-period SMA, signaling a potential long-term downtrend.
### Summary
The "US M2" indicator provides a comprehensive view of the US M2 money supply, highlighting significant trends and deviations. By combining short-term and long-term moving averages with amplified difference analysis, it offers valuable insights and trading signals based on macroeconomic liquidity conditions.
Equal Highs and LowsDescription:
The ‘Equal Highs and Lows’ indicator is a technical analysis tool that marks identical price levels on a trading chart using the current time-frame, assisting traders in identifying potential support and resistance zones or liquidity draws. It creates a horizontal line connecting points where the price has created equal highs and lows within a specified lookback period. Unique to this tool, it maintains a clean chart by removing the line once the price surpasses the equal highs or falls below the equal lows, ensuring only the currently relevant equal highs and lows are highlighted.
Features:
Customization Options: Users can adjust the appearance of the lines (color, width, and style) to match their chart setup or preferences. Users can also choose to extend the lines marking the equal highs/lows to the right of the chart making the equal high/low levels more easier to visualize.
User-Defined Lookback Length: The number of bars to look back for finding equal highs and lows can be set by the user, allowing for flexibility in different market conditions.
How It Works:
The indicator meticulously scans the chart over a user-specified lookback duration, identifying bars with matching high or low values that have not been mitigated on the current chat timeframe, thereby constructing an index of equal values. It subsequently connects these equal values on the chart with a line. While this intuitive indicator does not forecast future market trends, it emphasizes significant price levels derived from historical data.
Usage:
Identifying Support and Resistance: The lines drawn by the indicator can be used to identify potential support and resistance zones and/or draws of liquidity, which are crucial for making informed trading decisions.
Strategy Development: Traders can incorporate the visual cues provided by the indicator into their trading strategies, using them as one of the factors for entry or exit decisions.
Originality:
This indicator presents a distinctive method for pinpointing and illustrating equal highs and lows, granting traders a crucial insight into key price levels. It stands apart from conventional indicators by offering extensive personalization and employing a novel approach to augment chart analysis. Uniquely, it retains only unmitigated equal high/low levels on the chart, automatically discarding mitigated price levels once the price has reached that level.
Conclusion:
The "Equal Highs and Lows" indicator is a practical tool for traders looking to enhance their chart analysis with visual cues of significant price levels. Its customization options and innovative approach make it a valuable addition to the trading toolkit, suitable for various trading styles and strategies.
Stock Rating [TrendX_]# OVERVIEW
This Stock Rating indicator provides a thorough evaluation of a company (NON-FINANCIAL ONLY) ranging from 0 to 5. The rating is the average of six core financial metrics: efficiency, profitability, liquidity, solvency, valuation, and technical ratings. Each metric encompasses several financial measurements to ensure a robust and holistic evaluation of the stock.
## EFFICIENCY METRICS
1. Asset-to-Liability Ratio : Measures a company's ability to cover its liabilities with its assets.
2. Equity-to-Liability Ratio : Indicates the proportion of equity used to finance the company relative to liabilities.
3. Net Margin : Shows the percentage of revenue that translates into profit.
4. Operating Expense : Reflects the costs required for normal business operations.
5. Operating Expense Ratio : Compares operating expenses to total revenue.
6. Operating Profit Ratio : Measures operating profit as a percentage of revenue.
7. PE to Industry Relative PE/PB : Compares the company's PE ratio to the industry average.
## PROFITABILITY METRICS
1. ROA : Indicates how efficiently a company uses its assets to generate profit.
2. ROE : Measures profitability relative to shareholders' equity.
3. EBITDA : Reflects a company's operational profitability.
4. Free Cash Flow Margin : Shows the percentage of revenue that remains as free cash flow.
5. Revenue Growth : Measures the percentage increase in revenue over a period.
6. Gross Margin : Reflects the percentage of revenue exceeding the cost of goods sold.
7. Net Margin : Percentage of revenue that is net profit.
8. Operating Margin : Measures the percentage of revenue that is operating profit.
## LIQUIDITY METRICS
1. Current Ratio : Indicates the ability to cover short-term obligations with short-term assets.
2. Interest Coverage Ratio : Measures the ability to pay interest on outstanding debt.
3. Debt-to-EBITDA : Compares total debt to EBITDA.
4. Debt-to-Equity Ratio : Indicates the relative proportion of debt and equity financing.
## SOLVENCY METRICS
1. Altman Z-score : Predicts bankruptcy risk
2. Beneish M-score : Detects earnings manipulation.
3. Fulmer H-factor : Predicts business failure risk.
## VALUATION METRICS
1. Industry Relative PE/PB Comparison : Compares the company's PE and PB ratios to industry averages.
2. Momentum of PE, PB, and EV/EBITDA Multiples : Tracks the trends of PE, PB, and EV/EBITDA ratios over time.
## TECHNICAL METRICS
1. Relative Strength Index (RSI) : Measures the speed and change of price movements.
2. Supertrend : Trend-following indicator that identifies market trends.
3. Moving Average Golden-Cross : Occurs when a short-term MA crosses above mid-term and long-term MA which are determined by half-PI increment in smoothing period.
4. On-Balance Volume Golden-Cross : Measures cumulative buying and selling pressure.
Institutional Activity Index [AlgoAlpha]🌟 Introducing the Institutional Activity Index by AlgoAlpha 🌟
Welcome to a powerful new indicator designed to gauge institutional trading activity! This cutting-edge tool combines volume analysis with price movement to derive a unique index that shines a spotlight on potential institutional moves in the market. 🎯📈
Key Features:
🔍 Normalization Period : Adjust the look-back period for normalization to tailor the sensitivity to your trading strategy.
📊 Moving Average Types : Choose from SMA, HMA, EMA, RMA, WMA, or VWMA to smooth the index and pinpoint trends.
🌈 Color-Coded Trends : Instant visual feedback on index trend direction with customizable up and down colors.
🔔 Alerts : Set alerts for when the index shows increasing activity, decreasing activity, or has reached a peak.
Quick Guide to Using the Institutional Activity Index:
1. 📝 Add the Indicator: Add the indicator to favorites. Adjust the normalization period, MA type, and peak detection settings to match your trading style.
2. 📈 Market Analysis: Similar to volume that reflects the amount of collective trading activity, this index reflects an estimate of the amount of trading activity by institutions. A higher value means that institutions are trading the asset more, this can mean selling or buying as the indicator does not indicate direction . Look out for peak signals, which may indicate that institutions have already secured positions in preparation for a move in price.
3. 🔔 Set Alerts: Enable alerts to notify you when there is a significant change in the activity levels or a new peak is detected, allowing for timely decisions without constant monitoring.
How It Works: 🛠
It is common knowledge that institutions trade with high amounts of capital, but employ tactics so as to not move the price significantly when entering on positions. This can be done by entering in times of high liquidity so that when an institution buys, there are enough sellers to cancel out the price movements and prevent a huge pump in price and vice versa. The Institutional Activity Index calculates liquidity by measuring the volume relative to the price range (close-open). This value is smoothed using median and a user defined moving average type and period, enhancing its clarity. If normalization is enabled, the index is adjusted relative to its range over a user-defined period, making the data comparable across different conditions.
Embrace this innovative tool to enhance your trading insights and strategies! 🚀✨
HTF Matrix TableThis is a Higher Time Frame Table like the Intra-Day Table that I also have available.
ICT stresses time and liquidity levels in his teachings. This table helps to easily locate these key Time-based price levels. You can use these levels to determine your directional bias and to help generate your narrative for where the market is going.
This indicator creates a table that gives you the price for the following liquidity levels:
*Price* - Current Price
PMH - Previous Month High
PMO - Previous Month Open
PM MT - Previous Month Mean Threshold (Midpoint of candle body)
(Calculated by:
if pmo > pmc
pm_mt := ((pmo-pmc)/2)+pmc
if pmo < pmc
pm_mt := ((pmc-pmo)/2)+pmo)
PMC - Previous Month Close
PML - Previous Month Low
PWH - Previous Week High
PWO - Previous Week Open
PW MT - Previous Week Mean Threshold (Midpoint of candle body)
Calculated by:
if pwo > pwc
pw_mt := ((pwo-pwc)/2)+pwc
if pwo < pwc
pw_mt := ((pwc-pwo)/2)+pwo)
PWC - Previous Week Close
PWL - Previous Week Low
PDO - Previous Day Open
PDH - Previous Day High
PDL - Previous Day Low
PDC - Previous Day Close
PDEQ - Equilibrium of the previous day's range.
(Calculated by math.abs(((pdh-pdl)/2)+pdl))
PDH2 - Two Days Back High
PDL2 - Two Days Back Low
PDH3 - Three Days Back High
PDL3 - Three Days Back Low
Gives you the opening price for the following times:
Midnight Open
NY Open
Lets you set the time for the Asia and London sessions and will give the high and low for those two sessions.
Asia High
Asia Low
London High
London Low
Ability to hide either the table or lines.
The levels are sorted descending in price in the table, with the background colored based on their relation to price. The prices are also plotted on the chart based on the range you specify in relation to the current price. These lines are also colored based on their relation to price.
This indicator does not give you anything but the price at a specific time, you must determine your own bias and narrative based on the levels that are given.
The indicator runs on the seconds chart.
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
=========================================================================
فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Volume Profile / Order Blocks + Demandas e Ofertas FortesThis indicator combines two powerful technical analysis tools into one: the Volume Profile Bar-Magnified Order Blocks and Strong Demands and Offers.
The Volume Profile Bar-Magnified Order Blocks identifies and highlights significant areas of volume and price on the chart, helping traders identify zones of high liquidity and potential trend reversal areas. With advanced customization features such as choice of mitigation method and grid adjustments, traders can tailor the indicator to their individual preferences.
Alongside the Volume Profile, Strong Demands and Offers add an additional layer of analysis, highlighting points of interest where buying or selling pressure is strongest. This helps traders identify key areas where the balance of power may shift, providing potential entry or exit signals.
Key Features:
Automatic identification of significant volume areas.
Highlighting of zones of high liquidity and potential trend reversal areas.
Advanced customization, including choice of mitigation method and grid adjustments.
Highlighting of strong demands and offers to identify key areas of buying or selling pressure.
How to Use:
Add the indicator to your chart.
Adjust the parameters according to your preferences.
Observe the highlighted areas of volume and price on the chart.
Look for entry or exit signals based on the identified areas of interest.
This indicator is a valuable tool for traders looking to enhance their technical analysis based on volume and market dynamics. Try it out in your trading strategy and discover how it can help you make more informed and accurate decisions.
BINANCE-BYBIT Cross Chart: Spot-Perpetual CorrelationName: "Binance-Bybit Cross Chart: Spot-Perpetual Correlation"
Category: Scalping, Trend Analysis
Timeframe: 1M, 5M, 30M, 1D (depending on the specific technique)
Technical analysis: This indicator facilitates a comparison between the price movements shown on the Binance spot chart and the Bybit perpetual chart, with the aim of discerning the correlation between the two charts and identifying the dominant market trends. It automatically generates the corresponding chart based on the ticker selected in the primary chart. When a Binance pair is selected in the main chart, the indicator replicates the Bybit perpetual chart for the same pair and timeframe, and vice versa, selecting the Bybit perpetual chart as the primary chart generates the Binance spot chart.
Suggested use: You can utilize this tool to conduct altcoin trading on Binance or Bybit, facilitating the comparison of price actions and real-time monitoring of trigger point sensitivity across both exchanges. We recommend prioritizing the Binance Spot chart in the main panel due to its typically longer historical data availability compared to Bybit.
The primary objective is to efficiently and automatically manage the following three aspects:
- Data history analysis for higher timeframes, leveraging the extensive historical data of the Binance spot market. Variations in indicators such as slow moving averages may arise due to differences in historical data between exchanges.
- Assessment of coin liquidity on both exchanges by observing candlestick consistency on smaller timeframes or the absence of gaps. In the crypto market, clean charts devoid of gaps indicate dominance and offer enhanced reliability.
- Identification of precise trigger point levels, including daily, previous day, or previous week highs and lows, which serve as sensitive areas for breakout or reversal operations.
All-Time High (ATH) and All-Time Low (ATL) levels may vary significantly across exchanges due to disparities in historical data series.
This tool empowers traders to make informed decisions by leveraging historical data, liquidity insights, and precise trigger point identification across Binance Spot and Bybit Perpetual market.
Configuration:
EMA length:
- EMA 1: Default 5, user configurable
- EMA 2: Default 10, user configurable
- EMA 3: Default 60, user configurable
- EMA 4: Default 223, user configurable
- Additional Average: Optional display of an additional average, such as a 20-period average.
Chart Elements:
- Session separator: Indicates the beginning of the current session (in blue)
- Background: Indicates an uptrend (60 > 223) with a green background and a downtrend (60 < 223) with a red background.
Instruments:
- EMA Daily: Shows daily averages on an intraday timeframe.
- EMA levels 1h - 30m: Shows the levels of the 1g-30m EMAs.
- EMA Levels Highest TF: Provides the option to select additional EMA levels from the major timeframes, customizable via the drop-down menu.
- "Hammer Detector: Marks hammers with a green triangle and inverted hammers with a red triangle on the chart
- "Azzeramento" signal on TF > 30m: Indicates a small candlestick on the EMA after a dump.
- "No Fomo" signal on TF < 30m: Indicates a hyperextended movement.
Trigger Points:
- Today's highs and lows: Shows the opening price of the day's candlestick, along with the day's highs and lows (high in purple, low in red, open in green).
- Yesterday's highs and lows: Displays the opening price of the daily candlestick, along with the previous day's highs and lows (high in yellow, low in red).
You can customize the colors in "Settings" > "Style".
It is best used with the Scalping The Bull indicator on the main panel.
Credits:
@tumiza999: for tests and suggestions.
Thanks for your attention, happy to support the TradingView community.
[KVA] Custom Sessions Custom Sessions: Multi-Timeframe Analysis & Key Level Insights
Introduction:
Introducing " Custom Sessions," an innovative Pine Script indicator meticulously crafted to empower traders by offering an advanced level of analysis on various global trading sessions. This tool is designed not just to highlight trading sessions but to delve deeper into the nuances of market movements by analyzing candlestick behavior within those sessions, offering a nuanced view of market trends, liquidity, and potential turning points.
Core Features :
Session Customization : Tailor trading sessions to align with your strategy, focusing on the markets that matter most to you. Whether it's London, New York, Tokyo, Sydney, or Frankfurt, you have the control.
Enhanced Market Insight : Beyond session timing, gain a refined understanding of market dynamics through detailed candlestick analysis within each session, providing a granular view of price action.
Comprehensive Analysis Tools : Alongside session analysis, the indicator includes features like VWAP (Volume Weighted Average Price) and Fibonacci retracement levels, offering a multifaceted approach to market analysis across chosen timeframes.
VWAP : Gain insights into the market's trend and liquidity by viewing the Volume Weighted Average Price calculated for the custom timeframe.
Fibonacci Retracement Levels : Easily identify potential reversal points with automatically plotted Fibonacci levels at 0.236, 0.382, 0.5, 0.618, and 0.782for each candle
Real-Time Updates : As the market moves, so does " Custom Sessions," offering real-time insights that adapt to the unfolding market conditions.
Utilization Guide :
Configure Your Sessions : Begin by setting up the sessions that are most relevant to your trading approach, customizing their times as needed.
Select the Desired Timeframe : Input your preferred higher timeframe to analyze data that is most relevant to your trading strategy.
Dive into the Details : Use the detailed candlestick analysis within sessions to pinpoint potential entry and exit points, supported by VWAP and Fibonacci levels for deeper market insight.
Customize Your View : Adjust the visual aspects of the indicator, including session color coding and which elements to display, tailoring the tool to your preferences.
Acknowledgements :
A special thanks to Aurocks_AIF for their foundational work on "Sessions on Chart" . This project has been an invaluable resource, inspiring the development of " Custom Sessions" and pushing the boundaries of traditional session analysis.
Final Thoughts :
" Custom Sessions" is more than just an indicator; it's a comprehensive analysis tool that brings a new depth to the understanding of market sessions. By offering detailed insights into the behavior of candles within these sessions, along with essential analysis features, this indicator is a must-have for traders seeking to enhance their technical analysis arsenal.
Whether you're a day trader looking to capture short-term movements or a long-term investor seeking broader market insights, this indicator offers valuable data visualization to enhance your trading decisions. By integrating highs, lows, VWAP, and Fibonacci levels into your analysis, you gain a comprehensive view of market behavior across different timeframes and sessions
HolidayLibrary "Holiday"
- Full Control over Holidays and Daylight Savings Time (DLS)
The Holiday Library is an essential tool for traders and analysts who engage in backtesting and live trading . This comprehensive library enables the incorporation of crucial calendar elements - specifically Daylight Savings Time (DLS) adjustments and public holidays - into trading strategies and backtesting environments.
Key Features:
- DLS Adjustments: The library takes into account the shifts in time due to Daylight Savings. This feature is particularly vital for backtesting strategies, as DLS can impact trading hours, which in turn affects the volatility and liquidity in the market. Accurate DLS adjustments ensure that backtesting scenarios are as close to real-life conditions as possible.
- Comprehensive Holiday Metadata: The library includes a rich set of holiday metadata, allowing for the detailed scheduling of trading activities around public holidays. This feature is crucial for avoiding skewed results in backtesting, where holiday trading sessions might differ significantly in terms of volume and price movement.
- Customizable Holiday Schedules: Users can add or remove specific holidays, tailoring the library to fit various regional market schedules or specific trading requirements.
- Visualization Aids: The library supports on-chart labels, making it visually intuitive to identify holidays and DLS shifts directly on trading charts.
Use Cases:
1. Strategy Development: When developing trading strategies, it’s important to account for non-trading days and altered trading hours due to holidays and DLS. This library enables a realistic and accurate representation of these factors.
2. Risk Management: Trading around holidays can be riskier due to thinner liquidity and greater volatility. By integrating holiday data, traders can better manage their risk exposure.
3. Backtesting Accuracy: For backtesting to be effective, it must simulate the actual market conditions as closely as possible. Incorporating holidays and DLS adjustments contributes to more reliable and realistic backtesting results.
4. Global Trading: For traders active in multiple global markets, this library provides an easy way to handle different holiday schedules and DLS shifts across regions.
The Holiday Library is a versatile tool that enhances the precision and realism of trading simulations and strategy development . Its integration into the trading workflow is straightforward and beneficial for both novice and experienced traders.
EasterAlgo(_year)
Calculates the date of Easter Sunday for a given year using the Anonymous Gregorian algorithm.
`Gauss Algorithm for Easter Sunday` was developed by the mathematician Carl Friedrich Gauss
This algorithm is based on the cycles of the moon and the fact that Easter always falls on the first Sunday after the first ecclesiastical full moon that occurs on or after March 21.
While it's not considered to be 100% accurate due to rare exceptions, it does give the correct date in most cases.
It's important to note that Gauss's formula has been found to be inaccurate for some 21st-century years in the Gregorian calendar. Specifically, the next suggested failure years are 2038, 2051.
This function can be used for Good Friday (Friday before Easter), Easter Sunday, and Easter Monday (following Monday).
en.wikipedia.org
Parameters:
_year (int) : `int` - The year for which to calculate the date of Easter Sunday. This should be a four-digit year (YYYY).
Returns: tuple - The month (1-12) and day (1-31) of Easter Sunday for the given year.
easterInit()
Inits the date of Easter Sunday and Good Friday for a given year.
Returns: tuple - The month (1-12) and day (1-31) of Easter Sunday and Good Friday for the given year.
isLeapYear(_year)
Determine if a year is a leap year.
Parameters:
_year (int) : `int` - 4 digit year to check => YYYY
Returns: `bool` - true if input year is a leap year
method timezoneHelper(utc)
Helper function to convert UTC time.
Namespace types: series int, simple int, input int, const int
Parameters:
utc (int) : `int` - UTC time shift in hours.
Returns: `string`- UTC time string with shift applied.
weekofmonth()
Function to find the week of the month of a given Unix Time.
Returns: number - The week of the month of the specified UTC time.
dayLightSavingsAdjustedUTC(utc, adjustForDLS)
dayLightSavingsAdjustedUTC
Parameters:
utc (int) : `int` - The normal UTC timestamp to be used for reference.
adjustForDLS (bool) : `bool` - Flag indicating whether to adjust for daylight savings time (DLS).
Returns: `int` - The adjusted UTC timestamp for the given normal UTC timestamp.
getDayOfYear(monthOfYear, dayOfMonth, weekOfMonth, dayOfWeek, lastOccurrenceInMonth, holiday)
Function gets the day of the year of a given holiday (1-366)
Parameters:
monthOfYear (int)
dayOfMonth (int)
weekOfMonth (int)
dayOfWeek (int)
lastOccurrenceInMonth (bool)
holiday (string)
Returns: `int` - The day of the year of the holiday 1-366.
method buildMap(holidayMap, holiday, monthOfYear, weekOfMonth, dayOfWeek, dayOfMonth, lastOccurrenceInMonth, closingTime)
Function to build the `holidaysMap`.
Namespace types: map
Parameters:
holidayMap (map) : `map` - The map of holidays.
holiday (string) : `string` - The name of the holiday.
monthOfYear (int) : `int` - The month of the year of the holiday.
weekOfMonth (int) : `int` - The week of the month of the holiday.
dayOfWeek (int) : `int` - The day of the week of the holiday.
dayOfMonth (int) : `int` - The day of the month of the holiday.
lastOccurrenceInMonth (bool) : `bool` - Flag indicating whether the holiday is the last occurrence of the day in the month.
closingTime (int) : `int` - The closing time of the holiday.
Returns: `map` - The updated map of holidays
holidayInit(addHolidaysArray, removeHolidaysArray, defaultHolidays)
Initializes a HolidayStorage object with predefined US holidays.
Parameters:
addHolidaysArray (array) : `array` - The array of additional holidays to be added.
removeHolidaysArray (array) : `array` - The array of holidays to be removed.
defaultHolidays (bool) : `bool` - Flag indicating whether to include the default holidays.
Returns: `map` - The map of holidays.
Holidays(utc, addHolidaysArray, removeHolidaysArray, adjustForDLS, displayLabel, defaultHolidays)
Main function to build the holidays object, this is the only function from this library that should be needed. \
all functionality should be available through this function. \
With the exception of initializing a `HolidayMetaData` object to add a holiday or early close. \
\
**Default Holidays:** \
`DLS begin`, `DLS end`, `New Year's Day`, `MLK Jr. Day`, \
`Washington Day`, `Memorial Day`, `Independence Day`, `Labor Day`, \
`Columbus Day`, `Veterans Day`, `Thanksgiving Day`, `Christmas Day` \
\
**Example**
```
HolidayMetaData valentinesDay = HolidayMetaData.new(holiday="Valentine's Day", monthOfYear=2, dayOfMonth=14)
HolidayMetaData stPatricksDay = HolidayMetaData.new(holiday="St. Patrick's Day", monthOfYear=3, dayOfMonth=17)
HolidayMetaData addHolidaysArray = array.from(valentinesDay, stPatricksDay)
string removeHolidaysArray = array.from("DLS begin", "DLS end")
܂Holidays = Holidays(
܂ utc=-6,
܂ addHolidaysArray=addHolidaysArray,
܂ removeHolidaysArray=removeHolidaysArray,
܂ adjustForDLS=true,
܂ displayLabel=true,
܂ defaultHolidays=true,
܂ )
plot(Holidays.newHoliday ? open : na, title="newHoliday", color=color.red, linewidth=4, style=plot.style_circles)
```
Parameters:
utc (int) : `int` - The UTC time shift in hours
addHolidaysArray (array) : `array` - The array of additional holidays to be added
removeHolidaysArray (array) : `array` - The array of holidays to be removed
adjustForDLS (bool) : `bool` - Flag indicating whether to adjust for daylight savings time (DLS)
displayLabel (bool) : `bool` - Flag indicating whether to display a label on the chart
defaultHolidays (bool) : `bool` - Flag indicating whether to include the default holidays
Returns: `HolidayObject` - The holidays object | Holidays = (holidaysMap: map, newHoliday: bool, holiday: string, dayString: string)
HolidayMetaData
HolidayMetaData
Fields:
holiday (series string) : `string` - The name of the holiday.
dayOfYear (series int) : `int` - The day of the year of the holiday.
monthOfYear (series int) : `int` - The month of the year of the holiday.
dayOfMonth (series int) : `int` - The day of the month of the holiday.
weekOfMonth (series int) : `int` - The week of the month of the holiday.
dayOfWeek (series int) : `int` - The day of the week of the holiday.
lastOccurrenceInMonth (series bool)
closingTime (series int) : `int` - The closing time of the holiday.
utc (series int) : `int` - The UTC time shift in hours.
HolidayObject
HolidayObject
Fields:
holidaysMap (map) : `map` - The map of holidays.
newHoliday (series bool) : `bool` - Flag indicating whether today is a new holiday.
activeHoliday (series bool) : `bool` - Flag indicating whether today is an active holiday.
holiday (series string) : `string` - The name of the holiday.
dayString (series string) : `string` - The day of the week of the holiday.
Cast ForwardThis indicator will not forecast price action. It will not predict price movement nor will it in any way predict the outcome of any trade you may take. This is not a signal for buying or selling. You must do your own back testing and analysis for trading.
Time and price are the two most important components of market data. Where was price at what time? To help visualize this question I created this indicator. It allows for the previous session data to be overlayed onto the chart offset forward 24 hours. What this means is that you have the high, (high/low)/2, and low of each candle plotted on top of your chart for the time frame of the current chart, but offset so that the data from the current candle has the data from the corresponding candle 24 hours prior lined up on the x-axis.
SMA Logic: I used the SMA (Simple Moving Average) function with a length of 1 to plot the data points without any smoothing to give the true values of the data.
For Intraday Charting
For Electronic Trading Hours:
In order to line up the data correctly, for intraday charts, I used the current chart timeframe and divided it into 1380 (number of minutes in the 23 hour futures market trading day) to set the data offset. Using the same math logic, this indicator also gives the correct correlated data on the 30 second time frame. If the chart time frame that is currently being used does not allow for correct data correlation (not a factor of 1380) it will not plot the data.
For Regular Trading Hours:
In order to line up the data correctly, for intraday charts, I used the current chart timeframe and divided it into 405 (number of minutes in the 6 hour 45 minutes New York regular session trading day, including the 15 minute settlement time) to set the data offset. This indicator also gives the correct correlated data on the 30 second time frame. If the chart time frame that is currently being used does not allow for correct data correlation (not a factor of 405) it will not plot the data.
For the Daily Chart:
This indicator plots a visualization of the 20-40-60 day IPDA data range; (The IPDA data range helps traders identify liquidity, price gaps, and equilibrium points in the market, providing insights for optimal trade entries and market structure shifts). It does this using the same SMA logic as the intraday plot. What this means is it offsets the historical data of the daily chart 20, 40, or 60 bars forward. You can plot any combination of the three on the chart at one time, but these will not show on the intraday chart. This allows for visualization of where the market will possibly seek liquidity, seek to rebalance, or seek equilibrium in the future.
