Dividend Payout RatioShows the dividend payout ratio for the specific stock.
The dividend payout ratio indicates if the dividend payout is sustainable in the long run. Therefore,
1. A dividend payout under 50% is considered sustainable. The line will be green
2. A dividend payout over 50% and under 100%, the line will be yellow, is considered a stock to investigate since the dividend payout may have to be cut in the future which will cause the stock price to crash.
3. A dividend payout over 100%, the line will be red, is considered unsustainable and the dividend payout will most likely be cut in the near future. It can take up to a few years for the dividend cut to happen if the financials do not improve.
If the dividend payout ratio is over 100%, this means that the company is paying a dividend amount over $1 for every $1 earned. Therefore, the company must borrow money or find another source to pay the dividend amount that the company cannot afford to pay with the current earnings.
Calculating the dividend payout ratio:
Divide dividend paid by earnings after tax and multiplying the result by 100%.
Analisi fondamentale
SPDR Relativ Sector MomentumThe SPDR Relativ Sector Momentum Indicator is designed to evaluate the momentum of key U.S. market sectors relative to the broader market, represented by the S&P 500 Index (SPY). This indicator uses momentum-based techniques to assess sector performance and highlight relative strength or weakness over a given period. It leverages rate of change (ROC) as the primary momentum measure and incorporates smoothing via a simple moving average (SMA).
Methodology
This measure is smoothed over a configurable length (default: 20 periods) to filter noise and highlight trends. Sector momentum is computed for 11 key SPDR ETFs:
• XLE: Energy
• XLB: Materials
• XLI: Industrials
• XLY: Consumer Discretionary
• XLP: Consumer Staples
• XLV: Healthcare
• XLF: Financials
• XLK: Technology
• XLC: Communication Services
• XLU: Utilities
• XLRE: Real Estate
Momentum for the SPY is calculated similarly and serves as a benchmark.
Visualization
The indicator displays relative momentum values in a structured table, with high-contrast colors for better readability. The table dynamically updates sector performance, allowing users to easily track which sectors are outperforming or underperforming SPY. Additionally, the relative momentum values are plotted as individual lines around a zero baseline, providing visual confirmation of trends.
Applications
1. Portfolio Allocation: By identifying leading and lagging sectors, investors can allocate resources to sectors with strong momentum and reduce exposure to weaker sectors.
2. Trend Identification: The zero baseline helps users distinguish between sectors with positive and negative relative momentum.
3. Momentum Trading: The indicator aids in trading strategies that capitalize on sector rotations by highlighting momentum shifts.
Theoretical Background
Momentum strategies are grounded in behavioral finance theory and empirical research. They exploit the tendency of securities with strong past performance to continue outperforming in the short term. Jegadeesh and Titman (1993) demonstrated that momentum strategies yield significant returns over intermediate horizons (3-12 months). Applying this framework to sectors enhances the granularity of momentum analysis.
Limitations
While momentum strategies have shown historical efficacy, they are prone to mean reversion during periods of market instability (Barroso & Santa-Clara, 2015). Moreover, sector ETFs may exhibit varying levels of liquidity and sensitivity to macroeconomic factors, affecting signal reliability.
References
1. Jegadeesh, N., & Titman, S. (1993). “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” The Journal of Finance.
2. Barroso, P., & Santa-Clara, P. (2015). “Momentum Has Its Moments.” Journal of Financial Economics.
3. Moskowitz, T. J., & Grinblatt, M. (1999). “Do Industries Explain Momentum?” The Journal of Finance.
This indicator provides a practical tool for evaluating sector-specific momentum dynamics, grounded in robust financial theory. Its modular design allows customization, making it a versatile instrument for momentum-based sector analysis.
Accumulated Funding RateAccumulated Funding Rate
for future contract -ve/+ve funding fees that indicate long and short opening so that price differance between Spot and Future is balance buy exchange funding between long and short holder
-ve rate means Short is high so short holder has to pay fees to Long to correction in Price and vise versa
so over the periode of time accumulated rate its indicates the Bubble which can be explode any time to Liquidation of inbalance Long/Short Ratio some time its take longer period but its indicated bubbles direction
maximum -ve rates indicate Short opened from long period of time so when its liquidate/exit
then price will be correct to its original price that was struck due Short holder over the time and then now market will liquidate/exit those unstable Short like 50X/25X leverage and correct the price
Year-over-Year % Change for PCEPILFEHello, traders!
This indicator is specifically for FRED:PCEPILFE , which is a 'Personal Consumption Expenditures (PCE) Index excluding food and energy.'
What this indicator does is compare the monthly data to that of the same month last year to see how it has changed over the year. This comparison method is widely known as YoY(Year-over-Year).
While I made this indicator to use for FRED:PCEPILFE , you may use it for different charts as long as they show monthly data.
FRED:PCEPILFE is one of the main measures of inflation the Federal Reserve uses.
You can see the YoY % change of the PCE Index excluding food and energy in the official website for the Bureau of Labor Statistics, but unfortunately, I couldn't find one in TradingView.
So instead, I decided to make my own indicator showing the changes using FRED:PCEPILFE .
The code is very simple: it compares the data to the data 12 points ago because 12 points would mean 12 months in this chart. We then multiply the result by 100 for percentage.
Doing so, we compare the current month to the same month of the previous year.
Because I am only interested in the YoY % Change of the index, I pulled the indicator all the way up, covering the original chart data entirely. (Or you could achieve the same by simply moving your indicator to the pane above. But this way, the original chart data is also visible.)
I hope this indicator helps you with your analysis. Feel free to ask questions if have any!
God bless!
US Treasury Yields ROC1. Motivation and Context
The yield curve, which represents the relationship between bond yields and their maturities, plays a pivotal role in macroeconomic analysis and market forecasting. Changes in the slope or curvature of the yield curve are often indicative of investor expectations about economic growth, inflation, and monetary policy. For example:
• Steepening curves may indicate economic optimism and rising inflation expectations.
• Flattening curves are often associated with slower growth or impending recessions.
Analyzing these dynamics with quantitative tools such as the rate of change (ROC) enables traders and analysts to identify actionable patterns in the market. As highlighted by Gürkaynak, Sack, and Wright (2007), the term structure of interest rates embeds significant economic information, and understanding its movements is crucial for both policy makers and market participants.
2. Methodology
2.1 Input Parameters
The script takes the following key input:
• ROC Period (roc_length): Determines the number of bars over which the rate of change is calculated. This is an adjustable parameter (14 by default), allowing users to adapt the analysis to different timeframes.
2.2 Data Sources
The yields of the US Treasury securities for different maturities are fetched from TradingView using the request.security() function:
• 2-Year Yield (TVC:US02Y)
• 5-Year Yield (TVC:US05Y)
• 10-Year Yield (TVC:US10Y)
• 30-Year Yield (TVC:US30Y)
These yields are central to identifying trends in short-term versus long-term rates.
2.3 Visualization
Plots: The ROC values for each maturity are plotted in distinct colors for clarity:
• 2Y: Blue
• 5Y: Yellow
• 10Y: Green
• 30Y: Red
Background Highlight: The script uses color-coded backgrounds to visualize the identified curve regimes:
• Bull Steepener: Neon Green
• Bear Steepener: Bright Red
• Bull Flattener: Blue
• Bear Flattener: Orange
2.4 Zero Line
A horizontal zero line is included as a reference point, allowing users to easily identify transitions from negative to positive ROC values, which may signal shifts in the yield curve dynamics.
3. Implications for Financial Analysis
By automating the identification of yield curve dynamics, this script aids in:
• Macroeconomic Forecasting:
Steepeners and flatteners are associated with growth expectations and monetary policy changes. For instance, Bernanke and Blinder (1992) emphasize the predictive power of the yield curve for future economic activity.
• Trading Strategies:
Yield curve steepening or flattening can inform bond market strategies, such as long/short duration trades or curve positioning.
4. References
1. Bernanke, B. S., & Blinder, A. S. (1992). “The Federal Funds Rate and the Channels of Monetary Transmission.” American Economic Review, 82(4), 901–921.
2. Gürkaynak, R. S., Sack, B., & Wright, J. H. (2007). “The U.S. Treasury Yield Curve: 1961 to the Present.” Journal of Monetary Economics, 54(8), 2291–2304.
3. TradingView Documentation. “request.security Function.” Retrieved from TradingView.
Thrax - Pullback based short side scalping⯁ This indicator is built for short trades only.
⤞ Pullback based scalping is a strategy where a trader anticipates a pullback and makes a quick scalp in this pullback. This strategy usually works in a ranging market as probability of pullbacks occurrence in ranging market is quite high.
⤞ The strategy is built by first determining a possible candidate price levels having high chance of pullbacks. This is determined by finding out multiple rejection point and creating a zone around this price. A rejection is considered to be valid only if it comes to this zone after going down by a minimum pullback percentage. Once the price has gone down by this minimum pullback percentage multiple times and reaches the zone again chances of pullback goes high and an indication on chart for the same is given.
⯁ Inputs
⤞ Zone-Top : This input parameter determines the upper range for the price zone.
⤞ Zone bottom : This input parameter determines the lower range for price zone.
⤞ Minimum Pullback : This input parameter determines the minimum pullback percentage required for valid rejection. Below is the recommended settings
⤞ Lookback : lookback period before resetting all the variables
⬦Below is the recommended settings across timeframes
⤞ 15-min : lookback – 24, Pullback – 2, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 5-min : lookback – 50, pullback – 1% - 1.5%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 1-min : lookback – 100, pullback – 1%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ Anything > 30-min : lookback – 11, pullback – 3%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
✵ This indicator gives early pullback detection which can be used in below ways
1. To take short trades in the pullback.
2. To use this to exit an existing position in the next few candles as pullback may be incoming.
📌 Kindly note, it’s not necessary that pullback will happen at the exact point given on the chart. Instead, the indictor gives you early signals for the pullback
⯁ Trade Steup
1. Wait for pullback signal to occur on the chart.
2. Once the pullback warning has been displayed on the chart, you can either straight away enter the short position or wait for next 2-4 candles for initial sign of actual pullback to occurrence.
3. Once you have initiated short trade, since this is pullback-based strategy, a quick scalp should be made and closed as price may resume it’s original direction. If you have risk appetite you can stay in the trade longer and trial the stops if price keeps pulling back.
4. You can zone top as your stop, usually zone top + some% should be used as stop where ‘some %’ is based on your risk appetite.
5. It’s important to note that this indicator gives early sings of pullback so you may actually wait for 2-3 candles post ‘Pullback warning’ occurs on the chart before entering short trade.
BTC Mercenary ModelBitcoin Market Cycle Evaluation Using Subjective Z-Scores
Introduction:
I've crafted a unique indicator for Bitcoin that synthesizes multiple market indicators into a single, actionable Z-score, aiming to offer insights into the current market cycle phase. Here's the methodology:
Methodology:
Alpha Validation: Each component indicator has been tested for its predictive power (alpha) against Bitcoin's market cycle peaks and troughs from at least the last two cycles. This ensures each indicator contributes meaningfully to our model.
Z-Score Synthesis: By converting each indicator's value into a Z-score, we normalize their contributions. The average of these Z-scores provides a refined signal, indicating whether Bitcoin is in an overbought or oversold state relative to historical norms.
Features:
Individual Indicator Customization: Users can tweak inputs to optimize each indicator's alpha, enhancing the model's predictive accuracy.
Historical Averages: The script provides visibility into how both technical and fundamental indicators have scored in the past, offering a benchmark for current conditions.
ROC Flexibility: Adjust the Rate of Change (ROC) period to suit your analysis timeframe, allowing for more personalized market cycle interpretation.
Indicators Integrated:
Fundamental:
MVRV (Market Value to Realized Value) - Measures market sentiment vs. actual value.
Bitcoin Thermocap - Relates Bitcoin's market cap to its transaction volume.
NUPL (Net Unrealized Profit/Loss) - Indicates holder's profit or loss status.
CVDD (Coin Days Destroyed) - Shows the movement of long-held coins.
SOPR (Spent Output Profit Ratio) - Highlights whether coins are being spent at a profit or loss.
Technical:
RSI (Relative Strength Index) - Identifies overbought/oversold conditions.
CCI (Commodity Channel Index) - Detects cyclical turns in Bitcoin's price.
Multiple Moving Averages - For trend analysis over various time frames.
Sharpe Ratio - Evaluates risk-adjusted return.
Pi Cycle Indicator - Predicts cycle tops based on moving average crossovers.
Hodrick-Prescott Filter - Separates trend from cycle in price data.
VWAP (Volume Weighted Average Price) - Provides a trading benchmark.
How It Works Together:
This model uses a weighted average of Z-scores from these indicators to give a comprehensive view of Bitcoin's market cycle. The Z-scores are not just summed but considered in context; for example, when fundamental indicators like MVRV suggest an overvaluation while technical ones like RSI indicate a near-term correction, the model's output reflects this nuanced interaction.
Future Developments:
The next step is to include sentiment analysis, potentially from social media or news sentiment, to further refine our cycle predictions.
Chart Example:
Symbol/Timeframe: BTCUSD on a daily chart.
Script Name: Bitcoin Cycle Z-Score Evaluator
Feedback Encouraged:
I'm eager to receive feedback on how this model could be further tailored or expanded for better market insights.
-CM
Spent Output Profit Ratio | JeffreyTimmermansSOPR
The "Spent Output Profit Ratio" , aka SOPR indicator is a valuable tool designed to analyze the profitability of spent Bitcoin outputs. SOPR is derived by dividing the selling price of Bitcoin by its purchase price, offering insights into market participants' profit-taking or loss-cutting behavior.
This script features two selectable SOPR metrics:
SOPR 30D: A 30-day Exponential Moving Average (EMA) for short-term trend analysis.
SOPR 365D: A 365-day EMA for assessing long-term profitability trends.
How It Works
Key Levels: The horizontal reference line at 1.0 acts as a critical threshold:
Above 1.0: Market participants are generally in profit, indicating bullish sentiment.
Below 1.0: Market participants are selling at a loss, often signaling bearish sentiment.
Background Colors
Green: Indicates bullish conditions when the selected SOPR value is above 1.
Red: Highlights bearish conditions when the value is below 1.
Dynamic Selection
Easily switch between SOPR 30D and SOPR 365D in the settings for tailored analysis.
Features
Customizable SOPR Selection: Toggle between 30-day and 365-day SOPR views based on your trading preferences.
Dynamic Label: A floating label displays the current SOPR value in real-time, along with the selected SOPR metric for easy monitoring.
Background Highlights: Visual cues for bullish and bearish conditions simplify chart interpretation.
Real-Time Alerts
Bullish Alerts: Triggered when the selected SOPR crosses above 1.
Bearish Alerts: Triggered when the selected SOPR crosses below 1.
Clean Visualization
The indicator includes a horizontal reference line and clear color schemes for easy trend identification.
The SOPR Indicator is an essential tool for traders and analysts seeking to understand Bitcoin market sentiment and profitability trends. Whether used for short-term trades or long-term market analysis, this script provides actionable insights to refine your decision-making process.
-Jeffrey
[EAK]Median Growth% Hist. Vs Estimate=Indicator " Growth rate (Hist.VS Est.)" ซึ่งใช้แสดงอัตราการเติบโตของของบริษัท โดยเปรียบเทียบระหว่างข้อมูลในอดีต (Historical) กับการประมาณการ (Estimate) การตั้งค่าต่างๆ มีดังนี้
Inputs (ข้อมูลนำเข้า) : ส่วนนี้ใช้กำหนดรายละเอียดของข้อมูลที่นำมาคำนวณ
-Period (ช่วงเวลา): เลือกช่วงเวลาที่ต้องการวิเคราะห์ เช่น TTM (Trailing Twelve Months) คือ 12 เดือนล่าสุด หรือ FY ที่ใช้ข้อมูลของปีล่าสุด
-Show EPS Growth% (แสดง % การเติบโตทบต้นของ EPS): เลือกให้แสดงเปอร์เซ็นต์การเติบโตเฉลี่ยทบต้นของ EPS
-Show Median Growth% (แสดง % การเติบโตมัธยฐาน): เลือกให้แสดงมัธยฐานของการเติบโตเฉลี่ยทบต้น
-Show EPS Estimate by TradingView (แสดงการประมาณการ EPS โดย TradingView): แสดงข้อมูลการประมาณการ EPS จาก TradingView(เป็นการเรียกข้อมูลล่าสุดที่มีในเทรดดิ้งวิว ดังนั้นโปรดตรวจสอบ ว่าเป็นข้อมูลของปีไหน)
-Position (ตำแหน่ง): กำหนดตำแหน่งการแสดงผลของ Indicator บนหน้าจอ เช่น middle_rigth... (กลาง_ขวา)
-Text Size (ขนาดตัวอักษร): กำหนดขนาดตัวอักษรของข้อมูลที่แสดง เช่น normal (ปกติ)
โดยสรุป Indicator นี้ช่วยให้เห็นภาพรวมของการเติบโตของกำไรบริษัท โดยเปรียบเทียบอดีตกับการคาดการณ์ ทำให้วิเคราะห์แนวโน้มและตัดสินใจลงทุนได้ง่ายขึ้น และการตั้งค่าต่างๆ ช่วยให้ปรับแต่งการแสดงผลให้เหมาะสมกับการใช้งานของผู้ใช้
หมายเหตุ
EPSm=EPS CAGR(Median)
REVm=Revenue CAGR(Median)
OPm=Operating income CAGR(Median)
DIVm=Dividend CAGR(Median)
EQm=Total Equity CAGR(Median)
ASm=Total Asset CAGR(Median)
***Indicatorนี้ ออกแบบมาใช้กับ กราฟDay1 เท่านั้น โดยใช้การเรียกข้อมูลด้วยการนับBarย้อนหลัง อาจมีการผิดพลาดได้บ้าง ดังนั้นหากต้องการความแม่นยำที่สูงโปรดตรวจสอบข้อมูลกับแหล่งข้อมูลที่น่าเชื่อถืออีกครั้ง***
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Indicator " Growth rate (Hist.VS Est.)" is designed to display a company's growth rate by comparing historical data with estimates. The configuration options are as follows:
Inputs:
Period: Select the analysis period, such as TTM (Trailing Twelve Months), representing the last 12 months, or FY, which uses last full year data.
Show EPS Growth%: Enables the display of the compound annual growth rate (CAGR) of EPS.
Show Median Growth%: Enables the display of the median of the compound annual growth rate.
Show EPS Estimate by TradingView: Displays EPS estimate data from TradingView. (This retrieves the latest data available in TradingView; therefore, please verify the corresponding fiscal year.)
Position: Sets the indicator's display position on the chart, such as middle_right.
Text Size: Sets the text size of the displayed information, such as normal.
In summary, this indicator provides an overview of a company's earnings growth by comparing historical performance with forecasts, facilitating trend analysis and investment decisions. The various settings allow users to customize the display for their specific needs.
Note:
EPSm = EPS CAGR (Median)
REVm = Revenue CAGR (Median)
OPm = Operating income CAGR (Median)
DIVm = Dividend CAGR (Median)
EQm = Total Equity CAGR (Median)
ASm = Total Asset CAGR (Median)
***This indicator is designed for use on daily (D1) charts only. As it retrieves data by counting back bars, some inaccuracies may occur. For accuracy, please cross-reference the information with reliable sources.
Correlation Coefficient Master TableThe Correlation Coefficient Master Table is a comprehensive tool designed to calculate and visualize the correlation coefficient between a selected base asset and multiple other assets over various time periods. It provides traders and analysts with a clear understanding of the relationships between assets, enabling them to analyze trends, diversification opportunities, and market dynamics. You can define key parameters such as the base asset’s data source (e.g., close price), the assets to compare against (up to six symbols), and multiple lookback periods for granular analysis.
The indicator calculates the covariance and normalizes it by the product of the standard deviations. The correlation coefficient ranges from -1 to +1, with +1 indicating a perfect positive relationship, -1 a perfect negative relationship, and 0 no relationship.
You can specify the lookback periods (e.g., 15, 30, 90, or 120 bars) to tailor the calculation to their analysis needs. The results are visualized as both a line plot and a table. The line plot shows the correlation over the primary lookback period (the Chart Length), which can be used to inspect a certain length close up, or could be used in conjunction with the table to provide you with five lookback periods at once for the same base asset. The dynamically created table provides a detailed breakdown of correlation values for up to six target assets across the four user-defined lengths. The table’s cells are formatted with rounded values and color-coded for easy interpretation.
This indicator is ideal for traders, portfolio managers, and market researchers who need an in-depth understanding of asset interdependencies. By providing both the numerical correlation coefficients and their visual representation, users can easily identify patterns, assess diversification strategies, and monitor correlations across multiple timeframes, making it a valuable tool for decision-making.
On-Chain Analysis [LuxAlgo]The On-Chain Analysis tool offers a comprehensive overview of essential on-chain metrics, enabling traders and investors to grasp the underlying activity and sentiment within the cryptocurrency market. By integrating metrics like wallet profitability, exchange flows, on-chain volume, social sentiment, and more into your charts, users can gain valuable insights into cryptocurrency network behavior, spot emerging trends, and better manage risk in the cryptocurrency market.
🔶 USAGE
🔹 On-Chain Analysis
When analyzing cryptocurrencies, several fundamental metrics are crucial for assessing the value and potential of a digital asset. This indicator is designed to help traders and analysts evaluate the markets by utilizing various data gathered directly from the blockchain. The gathered on-chain data includes wallet profitability, exchange flows, miner flows, on-chain volume, large buyers/sellers, market capitalization, market dominance, active addresses, total value locked (TVL), market value to realized value (MVRV), developer activity, social sentiment, holder behavior, and balance types.
Use wallet profitability and social sentiment metrics to gauge the overall mood of the market, helping to anticipate potential buying or selling pressure.
On-chain volume and active addresses provide insights into how actively a cryptocurrency is being used, indicating network health and adoption levels.
By tracking exchange flows and holder balance types, you can identify significant moves by whales or institutions, which may signal upcoming price shifts.
Market capitalization and miner flows give you an understanding of the supply side of the market, aiding in evaluating whether an asset is overvalued or undervalued.
The distribution of holdings among retail investors, whales, and institutional groups can greatly influence market dynamics. A large concentration of holdings by whales may indicate the potential for significant price swings, given their capacity to execute substantial trades. A higher proportion of institutional investors often suggests confidence in the asset's long-term potential, as these entities typically conduct thorough research before investing. While retail participation indicates broader adoption, it also introduces higher volatility, as these investors tend to be more reactive to market fluctuations.
Understanding the balance and behavior of short-term traders, mid-term cruisers, and long-term hodlers helps traders and analysts predict market trends and assess the underlying confidence in a particular cryptocurrency.
🔶 DETAILS
This script includes some of the most significant and insightful metrics in the crypto space, designed to evaluate and enhance trading decisions by assessing the value and growth potential of cryptocurrencies. The introduced metrics are:
🔹 Wallet Profitability
Definition: Represents the percentage distribution of addresses by profitability at the current price.
Importance: Indicates potential selling pressure or reduced selling pressure based on whether addresses are in profit or loss.
🔹 Exchange Flow
Definition: The total amount of a cryptocurrency moving in and out of exchanges.
Importance: Large inflows to exchanges can indicate potential selling pressure, while large outflows might suggest accumulation or long-term holding.
🔹 Miner Flow
Definition: Tracks the inflow and outflow of funds by miners.
Importance: High inflows could indicate selling pressure, whereas low inflows or outflows might reflect miner confidence.
🔹 On-Chain Volume
Definition: The total value of transactions conducted on a blockchain within a specific period.
Importance: On-chain volume reflects actual usage of the network, indicating how actively a cryptocurrency is being utilized for transactions.
🔹 Large Buyers/Sellers
Definition: Tracks the number of large buyers (bulls) and sellers (bears) based on transaction volume.
Importance: Comparing the number of large buyers (bulls) to large sellers (bears) helps gauge market trends and sentiment.
🔹 Market Capitalization
Definition: The total value of a cryptocurrency's circulating supply, calculated by multiplying the current price by the total supply.
Importance: Market cap is a key indicator of a cryptocurrency’s size and market dominance. It helps compare the relative size of different cryptocurrencies.
🔹 Market Dominance
Definition: Market dominance represents a cryptocurrency’s share of the total market capitalization of all cryptocurrencies. It is calculated by dividing the market cap of the cryptocurrency by the total market cap of the cryptocurrency market.
Importance: Market dominance is a crucial indicator of a cryptocurrency's influence and relative position in the market. It helps assess the strength of a cryptocurrency compared to others and provides insights into its market presence and potential influence.
Special Consideration: Since BTC and ETH dominance is relatively high compared to other cryptocurrencies, specific adjustments are made during the presentation of values and charts. When analyzing BTC, the total market capitalization is used. For ETH analysis, BTC is excluded from the total market cap. For any other cryptocurrency besides BTC and ETH, both BTC and ETH are excluded from the total market cap to provide a more accurate view.
🔹 Active Addresses
Definition: The number of unique addresses involved in transactions within a specific period.
Importance: A higher number of active addresses suggests greater network activity and user adoption, which can be a sign of a healthy ecosystem.
🔹 Total Value Locked (TVL)
Definition: The total value of assets locked in a decentralized finance (DeFi) protocol.
Importance: TVL is a key metric for DeFi platforms, indicating the level of trust and the amount of liquidity in a protocol.
🔹 Market Value to Realized Value (MVRV)
Definition: A ratio comparing the market cap to realized cap.
Importance: A high ratio may indicate overvaluation (potential selling), while a low ratio could signal undervaluation (potential buying).
🔹 Developer Activity
Definition: The level of activity on a cryptocurrency’s public repositories (e.g., GitHub).
Importance: Strong developer activity is a sign of ongoing innovation, updates, and a healthy project.
🔹 Social Sentiment
Definition: The general sentiment or mood of the community and investors as expressed on social media and forums.
Importance: Positive sentiment often correlates with price increases, while negative sentiment can signal potential downtrends.
🔹 Holder Balance (Behavior)
Definition: Distribution of addresses by holding behavior: Traders (short-term), Cruisers (mid-term), and Hodlers (long-term).
Importance: Helps predict market behavior based on different holder types.
🔹 Holder Balance (Type)
Definition: Distribution of cryptocurrency holdings among Retail (small holders), Whales (large holders), and Investors (institutional players).
Importance: Assesses the potential impact of different user groups on the market. A more decentralized distribution is generally viewed as positive, reducing the risk of price manipulation by large holders.
These metrics provide a comprehensive view of a cryptocurrency’s health, adoption, and potential for growth, making them essential for fundamental analysis in the crypto space.
🔶 SETTINGS
The script offers a range of customizable settings to tailor the analysis to your trading needs.
🔹 On-Chain Analysis
On-Chain Data: Choose the specific on-chain metric from the drop-down menu. Options include Wallet Profitability, Exchange Flow, Miner Flow, On-Chain Volume, Large Buyers/Sellers (Volume), Market Capitalization, Market Dominance, Active Addresses, Total Value Locked, Market Value to Realized Value, Developer Activity, Social Sentiment, Holder Balance (Behavior), and Holder Balance (Type).
Smoothing: Set the smoothing level to refine the displayed data. This can help in filtering out noise and getting a clearer view of trends.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) and the length of the moving average for signal line calculation.
🔹 On-Chain Dashboard
On-Chain Stats: Toggle the display of the on-chain statistics.
Dashboard Size, Position, and Colors: Customize the size, position, and colors of the on-chain dashboard on the chart.
🔶 LIMITATIONS
Availability of on-chain data may vary and may not be accessible for all crypto assets.
🔶 RELATED SCRIPTS
Market-Sentiment-Technicals
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
XLimitless - Commitments of Traders (COT)XLimitless - Commitment of Traders (COT)
Unlock unparalleled market insights with the
XLimitless - COT Indicator, designed to give traders a competitive edge by visualizing the weekly Commitment of Traders (COT) data in an interactive and customizable table.
This advanced tool provides a comprehensive breakdown of market participants' positions, including Commercials, Non-Commercials (Large Speculators), and Non-Reportables (Small Speculators).
Key Features:
Customizable Data Display:
Choose from Commercial , Non-Commercial , or Non-Reportable positions.
Set the number of weeks to display (up to 52) for a tailored view.
Heatmap highlighting for quick identification of historical extremes.
Detailed Metrics:
Weekly Long, Short, and Net Positions data.
Open Interest and weekly changes for granular analysis.
Max/Min rows to spot historical highs and lows at a glance.
Interactive Table Positioning:
Flexible table placement options (e.g., Top Right, Bottom Left) to suit your chart layout.
Dynamic date adjustments with time-zone support for accurate alignment.
Enhanced Visual Feedback:
Heatmap-based color gradients for easy trend and extreme position identification.
Integrated tooltips for intuitive data understanding.
Global Asset Coverage:
Supports major asset classes, including Currencies, Commodities, Indices, and more.
Auto-detects base and quote currencies, ensuring accurate data mapping.
Historical Lookback Settings:
Analyze trends over 6 months to 5 years with configurable lookback periods.
Market Participants:
Commercial: Users & Producers
Non Commercial: Bank, Institutions & Large Traders
Non Reportable: Small Traders, Retail
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Disclaimer:
By using or publishing the XLimitless - Commitment of Traders (COT) indicator, you warrant that:
The information displayed and interpreted through this tool complies with applicable laws and regulations.
The indicator does not constitute investment advice or financial recommendations.
The content generated is not intended solely for qualified or professional investors.
Always ensure compliance with TradingView’s policies and applicable legal standards. Use this indicator responsibly and at your own discretion.
Z-Score Financial Market Conditions | JeffreyTimmermansZ-Score Financial Market Conditions
The Z-Score Financial Market Conditions indicator is a cutting-edge tool for measuring financial market stress and relaxation by combining eight critical financial metrics into a single composite Z-score. This dynamic indicator provides traders and analysts with actionable insights into the overall state of the financial markets, enabling informed decision-making across various trading and investment systems.
Purpose of the Indicator
This indicator serves as a comprehensive gauge of financial market conditions, offering a clear visualization of whether the markets are in a state of stress (elevated risks) or relaxation (normalized conditions). The Z-Score Financial Market Conditions tool is particularly effective for:
Macro-Level Risk Assessment: Identifying periods of high market stress or calmness.
Trend Following Systems: Gauging the market's underlying conditions to validate trends.
Mean Reversion Strategies: Using extreme Z-score levels to detect potential reversals.
Portfolio Risk Management: Adjusting asset exposure based on market-wide financial conditions.
This indicator works exclusively on the 1-day timeframe, as it is calibrated to analyze daily changes in the financial metrics that drive market behavior.
The Eight Key Components and Their Importance
The composite Z-score integrates the Z-scores of the following eight financial metrics. These metrics have been selected for their complementary insights into various aspects of financial market conditions:
VIX (S&P 500 Volatility Index)
Reflects implied volatility in the U.S. equity market.
High VIX values indicate increased uncertainty and risk aversion among market participants.
MOVE (US Treasury Bond Volatility Index)
Captures volatility in U.S. Treasury bonds.
Essential for understanding risk in fixed-income markets, which significantly impact broader economic conditions.
ICE BofA High Yield Option Adjusted Spread (BAMLH0A0HYM2)
Measures the risk premium for high-yield corporate bonds.
Rising spreads suggest increased credit risk and potential economic stress.
ICE BofA Corporate Index Option Adjusted Spread (BAMLC0A0CM)
Tracks credit spreads in the investment-grade bond market.
Helps evaluate the health of higher-quality corporate debt, a key indicator of financial stability.
ICE BofA US High Yield Index Spread (BAMLH0A0HYM2)
Focuses on high-yield U.S. corporate bonds.
Provides localized insights into U.S. credit conditions and risk levels.
CDS (Credit Default Swap Spreads)
Measures the cost of insuring against bond defaults.
Rising CDS spreads signal growing concern over creditworthiness, often a leading indicator of financial stress.
Global Bond Spread (AGG)
Represents global fixed-income spreads.
Offers a broader perspective on international financial conditions beyond the U.S. market.
TED Spread (Treasury-EuroDollar Spread)
The difference between interbank lending rates and short-term U.S. Treasury yields.
Widely regarded as an indicator of systemic risk in the banking sector.
Features and Improvements
This script builds upon the original concept by introducing advanced features to enhance its precision and usability:
Lookback Period Adjustment
A customizable lookback period for Z-score calculations (default: 160 days).
Allows for greater flexibility in adapting to different market conditions.
Moving Average (MA) Smoothing
Optional smoothing of Z-scores using an exponential moving average (EMA) for enhanced clarity.
Default smoothing length: 8 days.
Individual Component Visibility
Plots for individual Z-scores can be enabled or disabled to focus on specific metrics.
Dynamic Background Coloring
Visual cues to indicate bullish (green) or bearish (red) financial conditions based on the composite Z-score.
Custom Inputs
Toggle on/off for each financial metric to tailor the indicator to specific use cases.
Customizable parameters for smoothing and moving averages.
Applications
This indicator is versatile and can be effectively used in various trading systems and strategies:
Long-Term Investment Decision-Making: Assess macroeconomic trends for portfolio rebalancing.
Systematic Trading: Incorporate market conditions into algorithmic models to enhance robustness.
Volatility-Based Strategies: Use Z-score fluctuations to anticipate periods of market turbulence or calm.
Credits
This indicator was inspired by and builds upon the work of TomasOnMarkets . While incorporating significant enhancements, it acknowledges the foundational concepts provided by this original source. Thank you for sharing your input on this important indicator. We are honored to use it and to further improve upon it.
-Jeffrey
Dynamic Risk-Adjusted Performance Ratios with TableWith this indicator, you have everything you need to monitor and compare the Sharpe ratio, Sortino ratio, and Omega ratio across multiple assets—all in one place. This tool is designed to help save time and improve efficiency by letting you track up to 15 assets simultaneously in a fully customizable table. You can adjust the lookback period to fit your trading strategy and get a clearer picture of how your assets perform over time. Instead of switching between charts, this indicator puts all the critical information you need at your fingertips.
Sharpe Ratio -
Helps evaluate the overall efficiency of investments by comparing the average return to the total risk (measured by the standard deviation of all returns). Essentially, it tells you how much excess return you’re getting for each unit of risk you’re taking. A higher Sharpe ratio means you’re getting better risk-adjusted performance—something you’ll want to aim for in your portfolio.
Sortino Ratio -
Goes a step further by focusing only on downside risk—because let’s face it, no one worries about positive volatility. This ratio is calculated by dividing the average return by the standard deviation of only the negative returns. Perfect for those concerned about avoiding losses rather than chasing extreme gains. It gives you a sharper view of how well your assets are performing relative to the risks you’re trying to avoid.
Omega Ratio -
Offers a unique perspective by comparing the sum of positive returns to the absolute sum of negative returns. It’s a straightforward way to see if your wins outweigh your losses. A higher Omega ratio means your positive returns significantly exceed the downside, which is exactly what you want when building a strong, reliable portfolio.
This indicator is perfect for traders who want to streamline their decision-making process and gain an edge. Bringing together these three critical ratios into a single user-defined table makes it easy to compare and rank assets at a glance. Whether optimizing a portfolio or looking for the best opportunities, this tool helps you stay ahead by focusing on risk-adjusted returns. The customizable lookback period lets you tailor the analysis to fit your unique trading approach, giving you insights that align with your goals. If you’re serious about making data-driven decisions and improving your trading outcomes, this indicator is a game-changer for your toolkit.
Data TransformerIt is a data transformer. Is something TradingView lacks right now.
It is simple, it lets you transform the symbol of the chart into this options:
% change
change
QoQ change
QoQ change %
YoY change
YoY change %
Drawdawn %
Drawdawn
Cumulative
DCA Buy v1Key Features
1. Selective Entry Filters
Trend Filter
Enabled through "Enable Trend Filter?" using the "EMA Length" setting to ensure entries align with prevailing trends.
Momentum Filter
Configured using "Enable Momentum Filter?" combined with "RSI Length" and "RSI Source" to detect oversold conditions.
Bollinger Filter
Activated via "Enable Bollinger Filter?" along with "BB Length" and "BB Multiplier" to focus entries on deeper price dips below Bollinger Bands.
2. DCA Configuration
Base Order Settings
Choose between a percentage ("Base Order % of Equity/Initial Capital") or fixed value ("Base Order Value ($)").
Safety Order Settings
Fine-tune "Initial Deviation (%)" and "Price Deviation Multiplier" to control the spacing of safety orders.
Use "Volume Scaling Factor (Qty)" to scale the size of each subsequent safety order.
Customize the "First Safety Order Type" as either value-based or a multiplier of the base order using "1st Safety Order Value ($)" or "1st Safety Order Multiplier (Qty)".
Set the maximum number of safety orders through "Max Safety Orders".
3. Profit and Risk Management
Take Profit Settings
"Take Profit (%)" triggers a sell when a specific profit percentage above the average entry is reached.
Use "Trailing Take Profit (%)" to lock in profits while capturing additional upside if prices continue to rise.
Stop Loss Settings
Configure "Stop Loss (%)" to prevent excessive drawdowns by closing all positions when prices drop below a defined percentage.
4. Time Control & Visualization
Time Filters
Define trading windows with "Start Time" and "End Time".
Use "Cooldown (Seconds)" to avoid frequent entries during rapid price movements.
Visualization
Enable "Show Average Entry Price", "Show Take Profit Level", and "Show Stop Loss Level" to plot key levels on the chart for better monitoring.
5. Performance Metrics
Built-in performance tracking includes:
Net Profit (%): Measures overall profitability.
Win Rate (%): Displays the ratio of winning trades.
Max Drawdown (%): Tracks the largest equity decline.
Trading Days: Calculates the duration of active trades.
Profit/Day (%): Evaluates daily returns.
The performance table also shows average cycle duration and utilization of available capital.
WMA Killer Ratio Analysis | JeffreyTimmermansWMA Killer Ratio Analysis
The WMA Killer Ratio Analysis is a highly responsive trend-following indicator designed to deliver quick and actionable insights on the ETHBTC ratio. By utilizing advanced smoothing methods and normalized thresholds, this tool efficiently identifies market trends. Let’s dive into the details:
Core Mechanics
1. Smoothing with Standard Deviations
The WMA Killer Ratio Analysis begins by smoothing source price data using standard deviations, which measure the typical variance in price movements. This creates dynamic deviation levels:
Upper Deviation: Marks the high boundary, indicating potential overbought conditions.
Lower Deviation: Marks the low boundary, signaling potential oversold conditions.
These levels are integrated with the Weighted Moving Average (WMA), filtering out market noise and honing in on significant price shifts.
2. Weighted WMA Bands
The WMA is further refined with dynamic weighting:
Upper Weight: Expands the WMA, creating an Upper Band to capture extreme price highs.
Lower Weight: Compresses the WMA, forming a Lower Band to reflect price lows.
This adaptive dual-weighting system highlights potential areas for trend reversals or continuations with precision.
3. Normalized WMA (NWMA) Analysis
The Normalized WMA adds a deeper layer of trend evaluation: It calculates the percentage change between the source price and its smoothed average. Positive NWMA values suggest overbought conditions, while negative NWMA values point to oversold conditions.
Traders can customize long (buy) and short (sell) thresholds to align signal sensitivity with their strategy and market conditions.
Signal Logic
Buy (Long) Signals: Triggered when the price remains above the lower deviation level and the NWMA crosses above the long threshold. Indicates a bullish trend and potential upward momentum.
Sell (Short) Signals: Triggered when the price dips below the upper deviation level and the NWMA falls beneath the short threshold. Suggests bearish momentum and a potential downward trend.
Note: The WMA Killer Ratio Analysis is most effective when paired with other forms of analysis, such as volume, higher time-frame trends, or fundamental data.
Visual Enhancements
The WMA Killer Ratio Analysis emphasizes usability with clear and dynamic plotting features:
1. Color-Coded Trend Indicators: The indicator changes color dynamically to represent trend direction. Users can customize colors to suit specific trading pairs (e.g., ETHBTC, SOLBTC).
2. Threshold Markers: Dashed horizontal lines represent long and short thresholds, giving traders a visual reference for signal levels.
3. Deviation Bands with Fill Areas: Upper and Lower Bands are plotted around the WMA. Shaded regions highlight deviation zones, making trend boundaries easier to spot.
4. Signal Arrows and Bar Coloring: Arrows or triangles appear on the chart to mark potential buy (upward) or sell (downward) points. Candlesticks are color-coded based on the prevailing trend, allowing traders to interpret the market direction at a glance.
Customization Options
Adjustable Thresholds: Tailor the sensitivity of long and short signals to your strategy.
Dynamic Weighting: Modify upper and lower band weights to adapt the WMA to varying market conditions.
Source Selection: Choose the preferred input for price data smoothing, such as closing price or an average (hl2).
The WMA Killer Ratio Analysis combines rigorous mathematical analysis with intuitive visual features, providing traders with a reliable way to identify trends and make data-driven decisions. While it excels at detecting key market shifts, its effectiveness increases when integrated into a broader trading strategy.
-Jeffrey
VWAP Valuation Model | JeffreyTimmermansVWAP Valuation Model
This indicator provides a powerful tool for traders looking to assess the value of an asset based on the VWAP (Volume Weighted Average Price) and the z-score. The VWAP Valuation Model is designed to give insights into the overbought or oversold condition of an asset by comparing the current price to a volume-weighted average over a defined period.
Key Features:
VWAP Baseline: The indicator calculates a volume-weighted moving average of the price, which serves as the core reference line for price analysis.
Z-Score: The z-score is calculated to determine how far the current price deviates from the mean, adjusted for volatility. This score helps identify overbought and oversold conditions.
Smoothing Option: Optionally, the indicator can be smoothed for better visualization, with the smoothing length being adjustable.
Real-time Data: The indicator provides real-time insights for multiple assets, such as Bitcoin (BTCUSD), Ethereum (ETHUSD), and Solana (SOLUSD), and can take the broader market performance (like the total crypto market) into account.
Z-Score Table: The indicator features an interactive table that provides valuable information on the z-scores of selected assets, allowing traders to quickly get an overview of market conditions. The table is strategically positioned above the chart for maximum visibility without interfering with the chart data.
Usage:
Overbought/Oversold: A z-score above +1.5 indicates overvaluation (overbought), while a score below -1.5 indicates undervaluation (oversold). This indicator helps in making informed trading decisions.
VWAP Range: The indicator offers a visual representation of the VWAP range, crucial for understanding price trends and market dynamics.
This indicator is ideal for investors interested in fundamental analysis while also needing technical insights to identify buy and sell opportunities. It helps to objectively assess market valuation and make well-informed decisions.
Important Note: This indicators works only in mean-reverting markets, not trending periods.
-Jeffrey
Z-Score + Valuation BTC | JeffreyTimmermansBTC Valuation Indicator with Z-Score Analysis
The BTC Valuation Indicator is a sophisticated tool designed to offer traders and analysts a deeper understanding of Bitcoin’s market valuation, empowering them to make more informed decisions. By utilizing a combination of key moving averages and a logarithmic trendline, along with advanced statistical analysis through the Z-Score Indicator, this tool provides a comprehensive view of Bitcoin’s potential undervaluation or overvaluation.
Key Features:
200MA/P (200-Day Moving Average to Price Ratio)
This component compares Bitcoin’s current price to its 200-day Simple Moving Average (SMA), offering insights into the long-term trend. A positive value signals a potential undervaluation of Bitcoin, while a negative value may indicate overvaluation.
Use case: Identifying long-term price trends to forecast potential buying or selling opportunities.
50MA/P (50-Day Moving Average to Price Ratio)
This ratio focuses on the short-term dynamics of Bitcoin’s price, comparing it to its 50-day SMA. It helps traders detect bullish or bearish trends in the immediate future.
Use case: Spotting short-term market movements and adjusting strategies accordingly.
LTL/P (Logarithmic TrendLine to Price Ratio)
This ratio incorporates Bitcoin’s historical age, using a logarithmic trendline to measure price movements against long-term expectations. A divergence from this trendline can signal potential overvaluation or undervaluation, assisting in aligning trading decisions with broader market trends.
Use case: Evaluating the overall trajectory of Bitcoin’s value over time and predicting significant market shifts.
Z-Score Indicator Integration:
The BTC Valuation Indicator utilizes the Z-Score, a powerful statistical measure, to assess how far each of the aforementioned ratios deviates from the mean. Z-Scores help standardize these ratios, allowing traders to gauge the severity of under or overvaluation compared to historical averages.
What is a Z-Score?
A Z-score measures how far a data point is from the mean in terms of standard deviations. A Z-score of 0 indicates the value is exactly at the mean, while a positive or negative score shows how much the value deviates from it. A higher Z-score signals a more significant deviation, potentially pointing to a market anomaly, while a Z-score near 0 indicates normal conditions.
For instance:
A Z-score above +2 indicates that Bitcoin may be overvalued, with the likelihood of a market correction or reversion to the mean.
A Z-score below -2 signals possible undervaluation, suggesting an upward trend may be on the horizon.
Z-Score and Market Volatility
The Z-Score Indicator can be used in conjunction with volatility measures, such as the CBOE Volatility Index (VIX), to forecast potential market volatility. Just as a Z-scored VIX above +2 suggests decreasing volatility and the possibility of an upward trend, a Z-scored VIX below -2 indicates increasing volatility and a potential downward trend. This parallel can be used to predict Bitcoin’s potential movements in times of market uncertainty.
How to Use:
The BTC Valuation Indicator, when paired with the Z-Score, provides a more refined statistical framework to analyze Bitcoin’s market conditions. This integration allows traders to assess the severity of potential trends and price anomalies, assisting in the identification of profitable entry and exit points.
Important Considerations:
No Guarantee of Market Predictions: While this indicator is a valuable tool for assessing market conditions, no indicator can guarantee future performance. Always consider multiple factors and use the indicator as part of a comprehensive strategy.
Market Dynamics:
As market conditions evolve, continuously refine your approach. Historical performance may not be indicative of future results, and traders should remain vigilant to changing trends and developments.
By combining the power of moving averages, logarithmic trend lines, and Z-scores, the BTC Valuation Indicator equips investors with a robust, data-driven approach to Bitcoin valuation, enhancing decision-making and enabling a more nuanced understanding of market dynamics.
-Jeffrey
Correlation Pro
Smart Correlation Pro is an indicator for assessing the correlation between two assets in the market. It analyzes correlation over a selected period and provides traders with flexible tools for making informed decisions.
Key Features:
1. Correlation coefficient (-1 to 1):
• 1: Perfect positive correlation (movement in the same direction).
• 0: No correlation (assets are independent).
• -1: Perfect negative correlation (movement in opposite directions).
2. Dynamic analysis:
• Changes the color of the line depending on the strength of the correlation:
• Green — high positive correlation.
• Red — high negative correlation.
• Gray — weak or no correlation.
3. Trading signals:
• Automatic alerts when important correlation levels are reached (> 0.8 or < -0.8).
• Visual cues for identifying potential entry points or risk diversification.
4. Customizable settings:
• Compare any two assets (e.g., BTC and ETH).
• Ability to choose the correlation calculation period.
Who it’s for:
• Traders analyzing coin movements in the cryptocurrency market.
• Investors looking for the strongest or weakest assets for their portfolio.
• Those working with hedging or diversification strategies.
How to Use:
1. Set the second asset in the indicator settings.
2. Analyze the correlation change on the chart:
• High positive correlation → similar price movement, opportunity for hedging.
• High negative correlation → opposite movement, suitable for diversification.
• Low correlation → independence of assets, opportunity to choose the stronger asset.
Benefits:
• Easy to use.
• Instant analysis of asset correlations.
• Increases decision-making accuracy in the market.
(Опис:
Smart Correlation Pro — це індикатор для оцінки взаємозв’язку між двома активами на ринку. Він аналізує кореляцію за обраним періодом та надає трейдерам гнучкі інструменти для ухвалення обґрунтованих рішень.
Основні можливості:
1. Коефіцієнт кореляції (-1 до 1):
• 1: Ідеальна позитивна кореляція (рух в одному напрямку).
• 0: Відсутність кореляції (активи незалежні).
• -1: Ідеальна негативна кореляція (рух у протилежних напрямках).
2. Динамічний аналіз:
• Змінює колір лінії залежно від сили кореляції:
• Зелений — висока позитивна кореляція.
• Червоний — висока негативна кореляція.
• Сірий — слабка або відсутня кореляція.
3. Сигнали для трейдингу:
• Автоматичні оповіщення при досягненні важливих рівнів кореляції (> 0.8 або < -0.8).
• Візуальні підказки для визначення можливих точок входу або диверсифікації ризиків.
4. Гнучкість налаштувань:
• Порівнюйте будь-які два активи (наприклад, BTC та ETH).
• Можливість обирати період розрахунку кореляції.
Кому підходить:
• Трейдерам, які аналізують рух монет на криптовалютному ринку.
• Інвесторам, що шукають найсильніші або найслабші активи для портфеля.
• Тих, хто працює з хеджуванням або диверсифікацією.
Як використовувати:
1. Встановіть другий актив у параметрах індикатора.
2. Аналізуйте зміну кореляції на графіку:
• Висока позитивна кореляція → схожий рух цін, можливість хеджування.
• Висока негативна кореляція → протилежний рух, підходить для диверсифікації.
• Низька кореляція → незалежність активів, можливість вибору сильнішого активу.
Переваги:
• Простота у використанні.
• Миттєвий аналіз взаємозв’язків між активами.
• Підвищує точність рішень на ринку.)
ROE BandROE Band shows the return on net profit from shareholders' equity and the formula for decomposition
ROE = ROA x CSL x CEL
ROE Band consists of 5 parts:
1. ROE (TTM) is the 12-month ROE calculation in "green"
2. Return on Equity (ROE) is the current quarterly net profit / the average of the beginning and ending periods of shareholders' equity in "yellow"
3. Return on Assets (ROA) is the current quarterly NOPAT (net profit before tax) / the average of the beginning and ending periods of total assets in "blue"
4. Capital structure leverage (CSL) is a financial measure that compares a company's debt to its total capital. It is calculated by taking the average of the beginning and ending periods of total assets / the average of the beginning and ending periods of shareholders' equity. The higher the CSL, the more deb, in. "red"
5. Common earnings leverage (CEL) is the proportion of net profit and NOPAT (net profit before tax), where a lower CEL means more tax, in "orange"
The "😱" emoji represents the value if it increases by more than or decreases by less than 20%, e.g.
- ROE(TTM), ROE, ROA, CEL is decreasing
- CSL is increasing
The "🔥" emoji represents the value if it increases by more than or decreases, e.g.
- ROE(TTM), ROE, ROA, CEL is increasing
- CSL is decreasing
Market Cap LevelsThis indicator zeroes in on those key “round number” market caps and marks them right on your price chart, converting cumbersome billions into crisp, easy-to-track figures (e.g., “10 B”). Instead of getting lost in massive numbers, you’ll instantly see whether a stock is flirting with a big valuation threshold.
Why It Matters & How Big Players Might Use It:
Round-Number Magnet: Institutions often treat nice, round market caps as psychological checkpoints. When a company edges near or beyond SEED_TVCODER77_ETHBTCDATA:5B , SEED_TVCODER77_ETHBTCDATA:10B , or even $500B, it can spark new waves of interest—or caution.
Behavioral Insights: These lines can act like magnets or barriers, hinting at spots where price action could shift if the broader market starts perceiving the company as hitting “the next major level.”
Clean Visuals, Quick Decisions: By placing these key valuations directly on your chart, you can instantly gauge whether a stock is hovering just below or sailing above a major capital milestone—no calculator needed.
